WO2008124511A1 - Computer system for rule-based clothing matching and filtering considering fit rules and fashion rules - Google Patents
Computer system for rule-based clothing matching and filtering considering fit rules and fashion rules Download PDFInfo
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- WO2008124511A1 WO2008124511A1 PCT/US2008/059278 US2008059278W WO2008124511A1 WO 2008124511 A1 WO2008124511 A1 WO 2008124511A1 US 2008059278 W US2008059278 W US 2008059278W WO 2008124511 A1 WO2008124511 A1 WO 2008124511A1
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- A—HUMAN NECESSITIES
- A41—WEARING APPAREL
- A41H—APPLIANCES OR METHODS FOR MAKING CLOTHES, e.g. FOR DRESS-MAKING OR FOR TAILORING, NOT OTHERWISE PROVIDED FOR
- A41H3/00—Patterns for cutting-out; Methods of drafting or marking-out such patterns, e.g. on the cloth
- A41H3/007—Methods of drafting or marking-out patterns using computers
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/06—Buying, selling or leasing transactions
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/06—Buying, selling or leasing transactions
- G06Q30/0601—Electronic shopping [e-shopping]
Definitions
- the present invention relates to computer systems for providing consumer access to databases of clothing items and in particular to computer systems that programmatically match clothing items with individual consumers' data, possibly including searching, sorting, ranking and filtering database items.
- a merchant compiles a database of their products and/or services, possibly including information about each product (size, color, type, description, price, etc.). Then the merchant provides consumers with an external electronic interface to that database, such as through a Web server, giving access to those consumers with Internet connectivity on their computers, computing devices, or telecommunication devices. Consumers can then review the merchant's available offerings, select items of interest, and even order them by interacting with the merchant's interface (e.g., selecting items and quantities, arranging for payment, arranging for delivery, etc.).
- fit can be inferred from a description. For example, the fit for a belt that is 38 inches long and one inch wide might be inferred from that description alone. However, for other items, such as a dress, fit might not be so straightforward and in some cases, the best approach is for the consumer to physically have the item and try it on, which is impossible with online shopping. Another difficulty is the wide variety of clothing items that can include garments, accessories, shoes, belts, etc. The complexity of online shopping is further compounded for the consumer trying to assemble an outfit, that is, a set of two or more clothing items intended to be used or worn together.
- One approach is to take measurements from the consumer, assume other measurements, and then custom make the desired clothing item according to tailoring assumptions and/or standard models. Because of the wide variety of human body shapes and garment types this may work well for some people but not others.
- Another approach is to have clothing items represented by geometric models: scan an image of the consumer (or the consumer herself), and then use computer graphics techniques to generate a combined image of the consumer and a geometric model of a garment in an attempt to show a simulation of how that consumer might look, if she were actually wearing that garment.
- Such an approach takes time and might require the consumer to "virtually" try on a great many clothing items - one after another.
- Another attempt to deal with these problems involves analyzing a wide range of a market population and then designing a range of body shapes and designs for a particular garment based on that population. For example, manufacturers might be directed to produce several shapes of a particular pant to offer different fit choices in pants given what the population for the market for such pants is estimated at. The problem is that this approach still relies on the trial and error of locating that pant and determining individually whether it is a good match.
- a server system accessible to users using client systems can match consumers with garments and provide an improved, online, clothes shopping system, where a consumer is presented with a personalized online clothing store, wherein the consumer using a consumer client system can browse a list of garments matching the consumer's dimensions, body shape, preferences and fashion needs, wherein the garments are also filtered so that those shown also match fit and fashion rules so that selected garments have a higher probability of both fitting and flattering.
- a computer implemented method may present garments to a consumer using a computer by reading a database of garments, wherein the database of garments includes parameters for at least some of the garments represented by records in the database of garments, the parameters including at least a garment type, reading data representing a plurality of garment types, the data including, for each type of the plurality of garment types, a set of tolerance ranges for that garment type, obtaining consumer measurements from the consumer or a source derived from the consumer, obtaining garment measurements for garments in the database of garments, comparing customer measurements to garment measurements, scoring garments from the database of garments based on garment measurements, customer measurements and the set of tolerance ranges for each garment based on its garment type, and presenting the consumer with a computer generated filtered listed of garments from the database of garments ordered, at least approximately, according to garment scores.
- the scores can take into account customer preferences determined based on customer inputs. Garment type and the set of tolerance ranges might be determined by input from a fashion expert. The filtering might be done using thresholds on scores. [0019]
- the clothes shopping system can be a computerized implementation of a consumer-garment matching method. In specific embodiments, the consumer-garment matching method comprises up to four processes: definition, categorization, match assessment, and personalized shopping.
- a definition process comprises defining: a) human body shapes, b) human body heights, c) garment types, d) fit rules, and e) fashion rules.
- seven body shapes are defined, six body heights are defined, sixteen garment types are defined, and a plurality of fit rules and fashion rules are defined.
- Each definition may include a plurality of data points, formulae, tolerances and/or tolerance ranges.
- the resultant definitions can be stored in computer database tables or similar data structures.
- a categorization process allows for the collection of individual consumer records and individual garment records into computer databases.
- a consumer record describes an individual consumer, including his or her body measurements and personal profile, e.g., clothing preferences (such as fabric color), preferred tolerances (such as snugness of fit), and the like.
- the process can categorize the consumer by body shape and height, and assign to the consumer's record a corresponding shape code and a corresponding height code, wherein the codes represent a specific one of such shapes or body height bins.
- a garment record describes an individual garment, including its measurements and profile, e.g., its color, fabric, tolerances, etc.
- Garments can be categorized by body shape, which is assigned to a garment record in the form of the corresponding shape code or codes. Additionally, garments can also be categorized by garment type, and a garment type code stored in the garment's garment record.
- a match assessment process compares a consumer's record to one or more garment records and produces a scored, sorted and filtered list of matching garments.
- the match assessment process applies a series of three filters: the measurement filter, the profile filter and the shape code filter.
- the measurement filter uses fit rules with tolerances to compare a consumer's measurements to a garment's measurements in order to determine if the garment would physically fit the consumer at various critical measurement points, taking into account the desired fit from the design's perspective and the consumer's desired fit.
- the measurement filter also computes a score (a "priority code"), indicating how well the garment fits the consumer.
- the profile filter uses fashion rules with tolerances to compare a consumer's profile and preferences with a garment's profile in order to determine if the garment suits and flatters the consumer and reflects the consumer's preferences for style and fit.
- the profile filter also computes the priority code score indicating how suitable the garment is for the consumer.
- the shape code filter compares the consumer's shape code with the garment's shape code(s) to determine if the garment's shape matches the consumer's body shape.
- a personalized shopping process presents a filtered and ranked list of matching garments for recommendation to the consumer in an individually customized online shopping environment.
- the consumer's personalized store the consumer may purchase recommended garments that have a high probability of fitting and flattering and suit the consumer's clothing preferences.
- FIG. 1 is an illustration of a clothes shopping system, in accordance with described embodiments.
- FIG. 2 is a simplified block diagram of a consumer-garment matching method, in accordance with described embodiments.
- FIG. 3 is a simplified block diagram of a definition process, in accordance with described embodiments.
- Figs. 4A-D illustrate height and length measurement techniques, in accordance with described embodiments.
- FIGs. 5a and 5b are simplified block diagrams of a categorization process, in accordance with described embodiments; Fig. 5a shows a consumer recording process and Fig. 5b shows a garment recording process.
- Fig. 6 is a simplified block diagram of a match assessment process, in accordance with described embodiments.
- Figs. 7-13 are flowcharts illustrating a match assessment process for a fitted dress, in accordance with described embodiments.
- Fig. 14 is an illustration of example output from a match assessment process, in accordance with described embodiments.
- FIG. 15 is an illustration of a garment display interface, in accordance with described embodiments.
- An improved online clothes shopping system is described herein, where a consumer is presented with a personalized online store that lists clothing items for sale that are most likely to fit and flatter that particular consumer and match that consumer's preferences for style and fit.
- the presented list of items is generated by a computerized garment-consumer matching method that matches the fit and fashion of individual clothing items to individual consumers.
- Clothing items are commonly thought to include garments (dresses, coats, pants, shirts, tops, bottoms, socks, shoes, bathing suits, capes, etc.), but might also include worn or carried items such as necklaces, watches, purses, hats, accessories, etc.
- worn or carried items such as necklaces, watches, purses, hats, accessories, etc.
- sized and fitted garments are the items being shopped for, but it should be understood that unless otherwise indicated, the present invention may be used for shopping for other clothing items as well.
- an outfit is a collection of two or more clothing items intended to be worn or used together.
- Fig. 1 is a high-level diagram depicting a clothes shopping system 100, which is a computer implementation of a consumer-garment matching method in accordance with one embodiment of the present invention.
- the clothes shopping system is a client-server system, i.e., an assemblage of hardware and software for data processing and distribution by way of networks, as those with ordinary skill in the art will appreciate.
- the system hardware may include, or be, a single or multiple computers, or a combination of multiple computing devices, including but not limited to: PCs, PDAs, cell phones, servers, firewalls, and routers.
- the term software involves any instructions that may be executed on a computer processor of any kind.
- the system software may be implemented in any computer language, and may be executed as compiled object code, assembly, or machine code, or a combination of these and others.
- the software may include one or more modules, files, programs, and combinations thereof.
- the software may be in the form of one or more applications and suites and may include low-level drivers, object code, and other lower level software.
- the software may be stored on and executed from any local or remote machine-readable media, for example without limitation, magnetic media (e.g., hard disks, tape, floppy disks, card media), optical media (e.g., CD, DVD), flash memory products (e.g., memory stick, compact flash and others), Radio Frequency Identification tags (RFID), SmartCardsTM, and volatile and non-volatile silicon memory products (e.g., random access memory (RAM), programmable read-only memory (PROM), electronically erasable programmable read-only memory (EEPROM), and others), and also on paper (e.g., printed UPC barcodes) .
- magnetic media e.g., hard disks, tape, floppy disks, card media
- optical media e.g., CD, DVD
- flash memory products e.g., memory stick, compact flash and others
- RFID Radio Frequency Identification tags
- SmartCardsTM Radio Frequency Identification tags
- volatile and non-volatile silicon memory products e
- Data transfer to the system and throughout its components may be achieved in a conventional fashion employing a standard suite of TCP/IP protocols, including but not limited to Hypertext Transfer Protocol (HTTP) and File Transfer Protocol (FTP).
- HTTP Hypertext Transfer Protocol
- FTP File Transfer Protocol
- XML extensible Markup Language
- Additional and fewer components, units, modules or other arrangement of software, hardware and data structures may be used to achieve the invention described herein.
- An example network is the Internet, but the invention is not so limited.
- a clothes shopping system 100 is comprised of three interconnecting areas: a consumer module 110, a manufacturer module 120, and an administrative backend 130,, all operating in a networked environment that may include local and/or wide area networks (LAN/WAN) 150, and the Internet 140.
- LAN/WAN local and/or wide area networks
- the administrative backend 130 uses administrator workstations 132, web servers 134, file and application servers 136, and database servers 138.
- the backend houses the consumer-garment matching software, the consumer and garment record databases 139a - 139b, definition & rules database 139c, and the online store website with all of its necessary ecommerce components, such as Webpage generators, order processing, tracking, shipping, billing, email and security.
- Administrator workstations allow for the management of the entire system and all of its parts, including the inputting and editing of data.
- the manufacturer module 120 uses software/hardware that allows a manufacturer to input data into the garment records that represent the garments the manufacturer makes. For example, for each garment of a particular size or SKU, a manufacturer enters the garment's dimensional measurements and profile data into the manufacturer module. This data may be entered manually via a workstation 122 or automatically by interfacing with the manufacturer's own internal systems, such as CAD systems 124 and PLM (product lifetime management) systems, and/or pattern making systems. This inputted garment data might then be subjected to the garment categorization process 220, as described herein. Additionally, the module may provide the manufacturer with computed output from the system, such as the shape codes of their various garments. The manufacturer may now employ the system's output in his manufacturing process; for example, to print shape code(s) on a garment's label or sales tag, or to electronically embed part or all of a garment's record in its RFID tag.
- CAD systems 124 and PLM product lifetime management
- the consumer module 110 is typically accessed by consumers via personal computers at home, school or office 112.
- the consumer module 110 may also be accessed through cellular phones 116, PDAs 114 and other networked devices, such as kiosks 118 in retail stores at malls, shopping centers, etc. It is through the consumer module 110 that a consumer can input her measurements, preferences and profile data into her consumer record. This inputted consumer data might then be subjected to the consumer categorization process 220, as described herein. And importantly, the consumer module enables the consumer to shop and buy at her personalized online clothes store.
- FIG. 2 is a simplified block-diagram depicting a consumer-garment matching method 200 and the data inputs, outputs and interdependence of its constituent processes: a definition process 210, a categorization process 220, a match assessment process 230, and a personalized shopping process 240, described herein.
- Fig. 3 depicts a definition process 210.
- the definition process defines a) human body shapes into a set of shapes (represented by shape codes 1 through 7 in this embodiment), b) human body heights into a set of heights (represented by height codes 1 through 6 in this embodiment), c) garment types (sixteen in this embodiment), d) fit rules, and e) fashion rules.
- Table 1 lists twenty-one such measurements as used in one embodiment of the present invention. Other embodiments may use more, fewer or different body measurements. A similar or identical set of measurements may also be used by the categorization process 220 when collecting body measurement data from any individual consumer via the consumer module 110. Note: The measurement reference numbers appearing in Table 1 will be subsequently used throughout this document to concisely write formulae. The lowercase “c" (for consumer) denotes these measurements are provided by the consumer, such as might result from personal manual measurements.
- Figs. 4A-4D depict the positions and techniques for acquiring body measurements to obtain data shown in Table 1, as an example.
- human body shapes are defined by a body shape defining process 212.
- the body shape defining process is a series of calculations establishing arithmetic and/or geometric relationships between the different body measurements to generate an outline of a body.
- the shape defining process considers front and side outlines in two and three dimensions for each measurement and evaluates the relative proportions of certain points on the torso including, but not limited to: the proportion of the shoulders to the hips, the shoulders to the bust, the bust to the waist, the waist to the hip, the proportion of the body mass that is in the front bisection of the body, etc.
- one of the calculations of the shape defining process might determine the value of the shoulder circumference minus the hip circumference. Referring to the measurement reference numbers in Table 1 , this calculation can be represented as the formula ICc - 5Cc. Another calculation is bust circumference minus front bust divided by bust circumference, i.e., (2Cc - 7Fc) / 2Cc. Table 2 lists the formulae and result names for the thirteen such calculations used by the shape defining process in one embodiment. Note: the two preceding example calculations can be found listed in Table 2 as Values 1 and 6 respectively.
- a shape code may be determined using the three-dimensional (3-D) lines of the body's measurements and relative proportions of height and girth of shoulders, bust, waist, high hips and hips and knee. Such 3-D measurements may be used to determine a curve for the shape of the body in 3-D. A comparison of the two 3-D measurements may be used to determine a body shape code geometrically.
- human body measurement data taken from representative samples of the human population and sub-populations form the inputs of the shape defining process 212.
- the sample body measurement data is statistically analyzed to discern clustered subsets within the population, each sharing common data values.
- Each body shape is defined by a core set of measurement values together with an acceptable range of deviation from the mean for each value. In one embodiment, there are seven such subsets named and coded as "Shape 1 " through "Shape 7". In other embodiments, there might be more or fewer shape codes.
- the height defining process is a series of calculations establishing arithmetic and/or geometric relationships between the total body height (1 IHc in Table 1) and hip circumference (5Cc).
- the sample data is statistically analyzed to discern clustered subsets within the population, each sharing common data values within an acceptable range of deviation from the mean for each value. In one embodiment there are six such subsets named and coded as "Height 1" through "Height 6". It should be noted that other embodiments might have more or fewer than six height codes.
- the definitions of the seven body shape codes and six body height codes are stored in the definitions & rules database 139c as maintained by database server 138. Thus, having been defined, these seven body shape codes may then be assigned by the categorization process 220 to individual consumers whose measurements fall within the range of values corresponding to any particular shape code. Similarly, the six body height codes may be assigned by the categorization process to individual consumers whose measurements fall within the range of values corresponding to any particular height code. Similarly, shape codes may also be assigned to individual garments and outfits.
- a garment's type will necessarily affect which measurements are considered. For example, while a jacket may have a shoulder circumference (ICg), a pair of pants would not.
- measurement tolerances will also vary by garment type. Since they are cut differently, a Straight Dress (D2) may have a different bust tolerance than a Fitted Dress (Dl). Because measurements and tolerances vary by garment type, each garment type has a corresponding Garment Type Definition Table, setting forth a generalized fit rule for that garment type.
- Table 5 is the Garment Type Definition Table for a Fitted Jacket as used in one embodiment.
- a garment type definition table specifies the measurements, tolerances and order of calculation to be used by the measurement filter 232 during a match assessment 230, as defined herein.
- Tolerances may be specified as discrete values, discrete percentages, a range of values or percentages, and/or an array of values or percentages.
- Tolerance specifications can have absolute or "fuzzy" values or ranges, and may use comparative operands, such as equal to, greater than, etc. Tolerance specifications might also vary by shape code.
- an individual garment may have idiosyncratic properties that are unique to that garment.
- a particular Fitted Dress may be made of very stretchy fabric giving its shoulder, bust and waist tolerances greater ranges than the standard tolerances specified by the Fitted Dress Definition Table (not pictured).
- the generalized fit rule and tolerances of a garment type definition table can be overridden by idiosyncratic rules and tolerances that are specified in an individual garment's garment record, as defined herein.
- Garment type definitions together with their fit rules and tolerances are stored in a definitions & rules database 139c as maintained by database server 138.
- the fashion rules comprise of multivariate comparisons of data including, but not limited to, shape and height codes, garment type, fabric color and pattern, hair and skin color, neckline, sleeve and pocket styles, etc.
- one fashion rule posits that for each body height there are certain skirt styles that are more flattering.
- Table 6a is a Height Code/Skirt Code Table listing skirt styles suitable for each height code, as used in one embodiment.
- Table 6b lists the skirt style names corresponding to the skirt code numbers referenced in Table 6a.
- Table 7a is a Shape Code/Neckline Style Table listing neckline styles suitable for each shape code as used in one embodiment.
- the Shape Codes are represented by the letters M-Y-S-H-A-P-E. Some neckline styles are not recommended (those preceded with "not"), while the remainder are recommended.
- Table 7b lists the neckline style names corresponding to the neckline code numbers referenced in Table 7a, in one example.
- tolerances that may be specified as discrete values, discrete percentages, a range of values or percentages, and/or an array of values or percentages.
- Tolerance specifications can have absolute or “fuzzy" values or ranges, and may use comparative operands, such as equal to, greater than, etc. Tolerance specifications might also vary by shape-code.
- the Fashion rules, tolerances and fashion suitability tables are stored by the definition process 210 in a definitions & rules database 139c as maintained by database server 138.
- a categorization process 220 provides a means to: collect data describing individual consumers and individual garments, categorize those consumers and garments by shape and/or height, and store the resulting consumer and garment records in computer databases.
- a consumer record 229a is data describing an individual consumer, including her body measurements and personal profile data, e.g., her clothing preferences (such as fabric color) together with her preferred tolerances (such as snugness of fit across the bust).
- a means is provided to categorize the consumer by body shape and height, and to store the corresponding shape code and height code in her record.
- a consumer may also be assigned a unique identification number.
- a garment record 229b is data describing an individual garment, including its measurements and profile, e.g., its color, fabric, tolerances, etc.
- a means is provided to categorize the garment by body shape, and assign the corresponding shape code or codes to its record. Additionally, the garment is categorized by garment type, and the corresponding garment type code is assigned to the garment's record. A garment may also be assigned a unique identification number.
- the consumer records 229a are stored by the categorization process 220 in a consumer database 139a, while garment records 229b are stored in a garment database 139b.
- the consumer and garment databases are maintained by database server 138.
- a categorization process 220 has two sub-processes: consumer recording 221 (Fig. 5a) and garment recording 222 (Fig. 5b).
- the consumer module 110 supplies the consumer measurement and profile data that form the inputs of the consumer recording process. (In practice, that data may also be input or edited via the administrative backend 130.)
- An individual consumer's body measurements such as those listed in Table 1 and depicted in Figs. 4A-4D, are input into a consumer shape categorization process 223.
- the consumer shape categorization process may be implemented using a series of calculations that establish arithmetic and/or geometric relationships between the different body measurements. These calculations closely follow the transforms of the shape defining process 212 used in the definition process 210 described above, but also included in the calculation is a best-fit analysis to determine which body shape the individual consumer most closely matches.
- the resulting shape code is assigned to the consumer and stored in her record 229a.
- a shape might also be generated by a combination of measurements and other profile questions, such as profile questions answered by the consumer (e.g., "is your stomach fuller than your bottom") or by a combination of profile questions without measurements.
- Jane accesses the consumer module 140 of the clothes shopping system 100 and avails herself of the opportunity to shop and learn her shape code. Following on-screen instructions she uses a tape measure to collect her body measurements and enters them into an online form. She also enters her other profile information. This data is sent to backend 130 for consumer recording. Jane's returned shape code may be displayed to her. She may also receive an email containing her shape code in a printable, machine-readable format, such as a barcode. The resultant shape code may be physically sent to Jane in a variety of forms, such as a printed receipt, or embedded along with all, or part, of her consumer record on a magnetic card, or a SmartCardTM, etc. It may also be forwarded to her cellular phone, e.g., as a data file or an executable program. A consumer's body measurements may also be collected automatically; for example, by a full-body scanner at a retail establishment.
- a consumer height categorization process 224 calculates a consumer's height code.
- the height categorization process calculates the relationship between the consumer's total height and her hip circumference (measurement references 1 IHc and 5Cc, respectively, in Table 1).
- Table 8 lists the calculations, as used in one embodiment, to assign a height code to a consumer.
- the assigned height code can be stored in the consumer's record 229a.
- An individual consumer's profile data as collected via the consumer module 110, are also input and stored in the consumer's record 229a.
- a consumer's profile is data describing an individual consumer, her clothing preferences and her preferred tolerances.
- the manufacturer module 120 supplies the garment measurements and profile data that form the inputs of the garment recording process 232. (In practice, that data may also be input or edited via the administrative backend 130.)
- the measurements of any particular garment may include values for all, or a subset, of those garment measurements listed earlier in Table 3. For different garment types there are different critical measurements. For example, a dress will have different measurement points than a jacket or pants. These measurements may be taken from the pattern guide, or be imported from the CAD representation in the manufacturer's cutting system, or manually from the garment itself.
- a garment's measurements are inputs to a garment shape categorization process 225.
- the garment shape categorization process may comprise a series of calculations that establish arithmetic and/or geometric relationships (expressed as curves) between the various garment measurements.
- the garment's curves derived from the measurements, are compared to the curves represented by each of the seven body shapes to determine whether the garment is suitable for one or more body shapes.
- the curves are compared in front, side and back profiles.
- the curves may also be compared three-dimensionally (i.e., 3-D) with the volume of the front half of a body shape being compared with the volume of the front half of the garment.
- a best-fit analysis determines which body shape or shapes the garment most closely matches, as it is possible for a garment to be appropriate for more than one body shape.
- the resulting shape codes are assigned to the garment and stored in its garment record 229b.
- An individual garment's profile data as collected via the manufacturer module 120, are also input and stored in the garment's record 229b.
- a garment's profile is data describing an individual garment. Table 10 lists an example of 23 such data points as used in one embodiment. Note: values given are examples and may in practice be represented by code numbers, arrays, ranges, etc.
- the consumer records 229a can be stored in a consumer database 139a, while garment records 229b can be stored in a garment database 139b.
- the consumer and garment databases can be maintained by database server 138.
- Fig. 6 depicts a match assessment process 230.
- the match assessment process may be carried out at the administrative backend 130 utilizing application 136, Web 134, database 138, and other servers.
- the match assessment process may be used to compare an individual consumer's record 229a with one, or more, garment records 229b.
- the match assessment process is conducted iteratively, i.e., by comparing the consumer's record to each garment's record in turn, until all garment records have been compared. This results in a scored, sorted and filtered list of those garments which match that consumer.
- the match assessment process might also be described formulaically as locating a person in an N-dimensional person space (P) based on their shape, measurements, etc., locate a garment in an N-dimensional garment space (G), repeat this for all the garments, to generate a mapping of person to garments, f : P — > G.
- the inputs of the match assessment process are a consumer record 229a obtained from the consumer database 139a as maintained by database server 138, and one, or more, garment records 229b obtained from the garment database 139b, also maintained by database server 138.
- the match assessment process 230 is comprised of three filters: a measurement filter 232, a profile filter 234, and a shape code filter 236.
- the output of the filters is a ranked and sorted listing of matching garments.
- the sorting is composed of seven "Holding Bins" 238 - one for each shape code, and a Bin D 239 - "Don't Display” i.e., discarded garments that do not fit the consumer.
- a garment is temporarily assigned a priority code (Profile Reference # 123Dg).
- the priority code determines a garment's rank within its holding bin 238. This is most useful for the personal shopping process 240, as described herein, where the priority code determines the order in which matching garments are displayed to the consumer.
- Table 1 1 lists the data that comprises Jane's consumer record, containing her Consumer ID, body measurements, height code, shape code, and profile data.
- Table 12 lists the data that comprises the dress' garment record, containing its Garment ID, measurements, shape code(s), and profile data. Note that the bust, waist and other tolerance values (28Dg thru 35Dg) are calculated by referencing tolerance ranges specified in the Garment Type Definition Table for a Fitted Dress (not shown). These garment tolerances indicate the designer's preferred fit for the garment; they should not be confused with the consumer's preferred tolerances (100 IDc - 1004Dc). Table 12. Example Fields of a Garment Record for a Dress
- the first step of a match assessment is to determine the garment's type.
- the garment is a Fitted Dress. Its type code (Table 12, item 103Dg) is "Dl”.
- retrieve the garment type definition table for a fitted dress from the definition & rules database 139c as maintained by database server 138.
- the garment type definition of a fitted dress (not pictured, but similar in format to Table 5) specifies which measurements, tolerances and order of calculation are used by the measurement filter.
- the data to populate a data structure containing garment data as illustrated in Table 12 might be provided all or in part by the garment vendors.
- garment vendors might provide size, height code, body shape, etc. in an uploadable file that is uploaded to populate garment records.
- a vendor module might be included to provide vendors with an interface to provide that data.
- the garment record is generated, in whole or part, from descriptions of the garment. This would allow, for example, automated processing of text and other descriptions of garments, perhaps from a vendor's web resources describing that vendor's garments and outfits. An example might be a collection of web pages or a database used for driving a web shopping system.
- shape codes might even be determined from the descriptions, such as by processing text describing a garment according to heuristics to arrive at temporary placeholder "estimate" shape codes (until a fashion reviewer reviews the assignment) or the final shape codes to drive usage, such as in a personal store application.
- measurement filter 232 compares the measurements of a garment with those of a consumer.
- the measurement filter may be comprised of four sets of comparisons: circumference comparisons, front comparisons, height comparisons, and length or other design parameters comparisons. Depending upon garment type, fewer comparisons may be made. For example, a pair of pants would not require a sleeve comparison.
- the measurement filter 232 determines if the consumer's body part can physically fit within the garment's part.
- a circumference comparison calculates the garment's circumference #Cg minus the corresponding consumer's circumference #Cc, as illustrated in the following formula for shoulder circumferences:
- measurement filter proceeds to the next comparison.
- the dress has a bust circumference (2Cg) of 34 and Jane's bust is 32 (2Cc).
- Measurement filter 232 processes the next data point - waist circumference (3C).
- step 722 the garment is discarded (step 722) and a match assessment is started on the next garment, if any. Since this dress fits Jane at all critical circumferences, measurement filter 232 proceeds to calculate the front comparisons.
- measurement filter 232 compares the front data points 6F through 1OF for garment and consumer.
- a front comparison calculates the garment front (#Fg) minus the consumer front (#Fc). This formula is for comparing shoulder front:
- the dress has a shoulder front (6Fg) of 19 and Jane's shoulder front (6Fc) is 18.
- the difference between the garment's shoulder front and the consumer's shoulder front is calculated:
- 1 is more than zero and less than, or equal to, the dress' shoulder tolerance (28Dg) times Jane's front shoulder (6Fc) divided by Jane's shoulder circumference (ICc):
- Measurement filter 232 proceeds to process the next data point - high hip front (9F).
- Measurement filter 232 proceeds to process the next data point, "hip front (1 OF)".
- step 822 If any of the above comparisons do not match, then the garment is discarded (step 822) and a match assessment is started on the next garment, if any. Since this dress fits Jane at all critical front comparisons, measurement filter 232 proceeds to calculate the height comparisons.
- measurement filter 232 processes the next data point. Otherwise, measurement filter 232 discards the current garment into Bin D and proceeds to assess the next garment, if any.
- a flowchart 900 of these calculations is depicted in Fig. 9.
- step 904 the difference evaluated by the height equation. For example, when Jane's knee height is 17 and the dress' desired length is 0,
- a match is found at step 904, and measurement filter 232 may proceed to the shoulders to waist height comparison ( 12H).
- measurement filter 232 calculates the difference between consumer shoulder height (12Hc) and consumer waist height (14Hc), using the formula:
- measurement filter 232 processes the next data point. Otherwise, measurement filter 232 discards the current garment (step 922) and proceeds to assess the next garment, if any.
- Measurement filter 232 may proceed to process sleeve comparisons at step 910.
- Measurement filter 232 now proceeds to sleeve length (23Dg).
- Match assessment process 230 may proceed to profile filter 234.
- a garment's priority code (123Dg) equals zero. However, during match assessment process 230, the priority code may be temporarily given a numerical value for ranking purposes. If a garment fails any profile filter comparison it is "penalized” by having a number added to its priority code. The priority code determines the order in which garments are recommended and displayed to the consumer in her personalized online store (unless other ordering overrides, such as by also organizing all suitable garments for that consumer into categories). The higher a garment's priority code, the less suitable it is for the consumer and the later it will be displayed to her. The lower a garment's priority code, the more likely it will be displayed. A garment with a priority code of "1" will be recommended and appear before a garment with a priority code of "5".
- a "1" is added to the priority code when any profile comparison fails. Note that the value of this penalty could be variable and weighted to a particular comparison. For example, failure to match a consumer's color preference may penalize a garment by 3, whereas failure to match a consumer's fabric preference may only penalize it by 2.
- each consumer profile data point may be assigned a secondary value, referred to as an "importance value", to indicate its relative importance to the consumer.
- Profile filter 234 compares the consumer's desired fit for certain circumferences. That is, the measurement filter's previous circumference comparisons may be re-run using the consumer's desired tolerances in lieu of the garment's tolerances. For example, a sweater may be designed to fit loosely across the bust, but the consumer prefers a snug fit at her bust. In that case the profile filter would re-run the bust circumference comparison using a snug tolerance value. Then if the sweater does not fit snugly at the consumer's bust, its priority code is incremented, thus penalizing the sweater but not entirely discarding it, because it still fits the consumer, albeit more loosely than she prefers.
- profile filter 234 runs a modified version of that circumference calculation, substituting the consumer's tolerance for the garment's tolerance.
- a flowchart 1000 of these desired fit comparisons is depicted in Fig. 10.
- step 1002 if the consumer shoulder tolerance (lOOlDc) is less than the garment shoulder tolerance (28Dg), then at step 1004, the shoulder circumference calculation is re-run by substituting the consumer's shoulder tolerance for the garment's shoulder tolerance. If at step 1006, the garment fails the recalculation, then the priority code is increased by one (step 1008) and the next comparison is performed. Therefore, the measurement filter's shoulder circumference comparison given earlier as:
- match assessment process 230 proceeds to the other profile comparisons with the dress' priority code still equaling zero.
- Match assessment process 230 compares these four consumer and garment data points as follows.
- the first data point is whether garment color (1 15Dg) is contained in the array of values in the consumer's color palette (1005Dc).
- the next data point is whether the garment style (1 18Dg) is contained in the array of values in the consumer's desires styles (1006Dc).
- the next data point is whether garment fabric (119Dg) is contained in the array of values in the consumer's desired fabrics (1007Dc).
- the next data point is whether garment retail price (107Dg) is less than or equal to consumer's "I usually spend" (1013Dg).
- match assessment process 230 proceeds to step 1104 and adds one to the garment's priority code each time a comparison fails.
- the weights assigned to each comparison might be different than one and/or vary from comparison to comparison.
- match assessment process 230 proceeds to the size comparison 1112 still having a priority code of zero.
- match assessment process 230 compares the garment's manufacturer size (121Dg) with the consumer's usual size (1012Dc). This is an array of size values dependent on garment type. As noted above, manufacturers' sizes are notoriously variable from manufacture to manufacturer and even internally inconsistent. A manufacturer often has its own proprietary sizing scheme, e.g., "A" versus "10.” So, a separate size lookup table (not shown here) is employed to normalize the garment's manufacturer size (121D) for use in the size comparison.
- the garment's manufacturer size (121Dg) is 1.
- the size lookup table indicates a "Smart Fashions" size 1 dress corresponds to a size 8.
- match assessment process 230 subtracts the garment's normalized manufacturer size from the consumer's usual size. If at step 1114, the difference is more than a size tolerance range of plus or minus 4, then match assessment process 230 adds one to the priority code.
- Steps 1112 & 1114 may be expressed by the following equation: ((1012Dc - 121Dg) > ⁇ 4).
- Jane's usual dress size is 10 and the dress' normalized manufacture's size is 8.
- ((10 - 8) > ⁇ 4) is FALSE. So, this dress is still a perfect match and its priority code is unchanged at zero.
- fashion rules and tolerances are defined in fashion suitability tables that are stored in a definitions and rules database 139c as maintained by database server 138.
- a plurality of such tables is employed during fashion suitability comparisons.
- a flowchart 1200 of the fashion suitability comparison calculations is depicted in Fig. 12.
- two fashion suitability comparisons will be made: height code-to-shirt style and shape code-to-neckline style.
- Match assessment process 230 compares two consumer and garment data points as follows. At step 1202, if the garment's skirt style (1 14Dg) is contained in the array of suitable values for the consumer's height code (as listed in Table 6a, for example). Then, at step 1206, if garment neckline style (1 10Dg) is contained in the array of suitable values for the consumer's shape code (as listed in Table 7a, for example), 3) then this garment is a match and its priority code is not changed.
- match assessment process 230 proceeds to step 1204 and adds 1 to the garment's priority code each time a fashion suitability comparison fails.
- Jane's height code 101Hc
- the garment's skirt style (1 14Dg) is "A-line", or skirt style code 1.
- an A-line skirt is suitable for a consumer with a height code of 2.
- Jane's shape code (lOOSc) is 5.
- the garment's neckline style (1 10Dg) is "crew/jewel”.
- a crew neckline style is suitable for a consumer with a shape code of 5.
- Figure 14 depicts holding bins 238, which form the final output of the match assessment process 230. As illustrated, there are seven holding bins, labeled 1 through 7; one for each body shape in this embodiment. In other embodiments, there may be more or fewer bins. In a specific embodiment, there are 42 bins for shape and height combinations.
- Figure 13 depicts a shape code filter 236.
- the shape code filter Based on the garment's shape code (100Sg), the shape code filter inserts the garment (represented by its ID) and its priority code into the bin or bins corresponding to its shape code(s) as illustrated in Figure 14.
- a garment's shape code may be an array of numbers, e.g., 3, 5, 7. In this case the garment would be placed in bins 3, 5 and 7. The garment is inserted into the bins by ascending order of its priority code. The garments are thus segregated by shape code, and ordered from most suitable to least suitable. Garments that share a consumer's shape code and have a priority code of zero are considered "best matches".
- Match assessment process 230 then proceeds to a match assessment of the next garment, if any. Otherwise, the match assessment process ends with the output being a scored, ranked, sorted and filtered list of those garments which match the consumer to various degrees. This list may be used by a personalized shopping process 240 for the purpose of displaying matching garments to the consumer. Further it may be stored as a table, keyed to the consumer's record in consumer database 139a, as maintained by database server 138.
- the dress' shape code is "1 , 5". So, it will be inserted into both holding bins 1 and 5. And it will be inserted at the very top of each bin, because its priority code equals zero. In Jane's personalized store, this dress may be recommended to her as a BEST match because the dress shares Jane's shape code of 5 and has a priority code of zero. Outfits
- a plurality of garments may be assembled into an outfit.
- one outfit may include three garments: a Fitted Jacket, a Straight Top and Fitted Pants.
- an outfit may be treated as a garment.
- an outfit has its own record in the garment database 139b.
- the outfit's record may contain pointers the records of its constituent garments.
- Outfits are also assigned their own shape codes by combining the shape codes of their constituent garments according to an outfit categorization process.
- outfits may also be included in a match assessment as described above. The consumer may be presented with both individual garments and outfits during the personalized shopping process.
- a personalized shopping process 240 presents a consumer with her personal online clothing store, where she may browse and purchase recommended garments that she can trust will fit and flatter her body and suit her clothing preferences.
- the consumer is presented with a personal store, which shows the customer garments, outfits and complementary accessories that match the customer's measurements, body shape, height code, personal preferences and fashion styling, that will fit her and flatter her as determined by the fashion suitability rules. Only those garments, outfits and complementary accessories that fit and flatter the consumer are displayed in her Personal Store. These items may be displayed in a plurality of modes; e.g., ranked by personal fashion preference, or price, or color, or seasonal trends, and so forth. And they may be displayed in any combination that the match assessment result allows.
- the consumer uses a kiosk in a retail store where the selection represents what is available in inventory at that moment on the floor and the consumer may print out and shop using a recommendation/personal selection.
- a consumer's personal online store is accessed through consumer module 110 of the clothes shopping system 100.
- Jane may shop at her online store by using a Web browser on her home PC.
- the online store utilizes typical and necessary ecommerce components, such as Webpage generators, order processing, tracking, shipping, billing, email, security, etc., not pictured here.
- the personal store may be implemented as a freestanding website served by a server system, or as a subsection within another website, or as a web service, or within a standalone application outside of a browser environment (e.g., a "widget” or "gadget”), or in some combination of the above.
- the results of a match assessment 230 of multiple garments and outfits may be displayed to the consumer using a graphical user interface (GUI) 1500 as depicted in Fig. 15.
- GUI graphical user interface
- Interface 1500 allows the consumer to quickly view and filter the results of a match assessment query.
- the garments may be displayed in garment area 1520.
- the priority code assigned each garment may be used to determine their order of display. For example, BEST-fit garments, those with a priority code of zero, may be displayed first.
- the consumer may "page" through the garments by selecting the page controls 1560.
- a garment may be displayed with picture(s), descriptive text, ordering information, shopping cart buttons, etc.
- the results of a match assessment may also be emailed to the consumer, delivered via cellular phone, PDA, physically mailed in the form of a personalized printed catalog, or other delivery methods.
- the consumer may wish to consider garments that are less-than-perfect matches for her. If so, those garments having priority codes greater than zero may then be displayed in the order of their suitability, according to priority code.
- the garment's priority code may be displayed as a code or as an icon by the interface in order to indicate to the consumer how suitable that garment is for her.
- the consumer may also browse garments of different body shapes.
- a shape control 1510 is a row of icons/text depicting the seven body shapes of this embodiment. Clicking on a body shape icon selects that shape and the remainder of the page 1512 is updated with garments matching that body shape.
- the GUI might provide an icon, scale, number line, or other graphical representation of a gauge for the consumer that indicates to the consumer how well the garment fits and where with respect to the garments' tolerances, the consumer's measurements fall, thus allowing the consumer to determine how snug is snug, etc.
- the GUI should provide an option to allow the consumer to purchase garments that are not within prespecified preferences.
- Additional filter controls 1570 may be displayed.
- a garment type (102Dg) filter lists the various types of matching garments, such as "Dresses.”
- a brand (106Dg) Filter lists brands and designers, such as “Smart Fashions”.
- a style (1 18Dg) filter lists clothing styles, such as "Romantic.”
- a filter could be displayed for any, or all, garment profile data points, such as color (115Dg), fabric (1 19Dg), sleeve style (1 12Dg), etc.
- interface 1500 will show all matching garments that are jackets.
- “checkbox” selection interface as those familiar in the art will appreciate. For example, Jane may click Skirts, Pants, Brand A, Romantic, and Artsy. The garment area 1520 may then be updated with garments meeting all of those selected filter options. Thus, the personal online store can fetch, sort and display matching garments in many useful ways. And thus, the consumer may purchase one or more garments, with confidence that the garments are likely to fit and flatter her. In fact, the consumer can, with one or more click, purchase and entire outfit with multiple components.
- the personal store can be shared with friends and family, indicating to them the filtered garments that fit and flatter, without needing to provide those others with fit information, size information, preferences, etc.
- elements of the systems described above can be expanded to cover a personal mall, wherein filtering is done as above, but over multiple online retail outlets.
- the particular retail outlets that are part of the system would depend on a number of criteria and the operator of the matching system might provide that access in exchange for commissions, as well as upselling, cross-marketing and providing other useful features for the consumer.
- An advantage to those retailers who join the personal mall and provide a virtual storefront is reduced return rates. With proper arrangement of the personal mall, each retail outlet can present its own brand and may be the shipper that ships the products directly to the consumer.
Abstract
Description
Claims
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JP2010502295A JP2010524090A (en) | 2007-04-06 | 2008-04-03 | Computer system for rule-based clothing matching and filtering, taking into account fit rules and fashion rules |
CA002662948A CA2662948A1 (en) | 2007-04-06 | 2008-04-03 | Computer system for rule-based clothing matching and filtering considering fit rules and fashion rules |
IL197583A IL197583A0 (en) | 2007-04-06 | 2009-03-12 | Computer system for rule-based clothing matching and filtering considering fit rules and fashion rules |
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Also Published As
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US20070198120A1 (en) | 2007-08-23 |
US7617016B2 (en) | 2009-11-10 |
EP2069977A1 (en) | 2009-06-17 |
AU2008237335A1 (en) | 2008-10-16 |
IL197583A0 (en) | 2009-12-24 |
JP2010524090A (en) | 2010-07-15 |
EP2069977A4 (en) | 2012-02-01 |
CA2662948A1 (en) | 2008-10-16 |
US20100023421A1 (en) | 2010-01-28 |
CN101548282A (en) | 2009-09-30 |
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