System and method for collaborative shopping, business and entertainment
Methods for product recommendation are provided. This includes collecting personal user data including profession, gender, size, preferences, user's apparel size, user's address, who the user's friend are, user's friends' information, users' medical records including eyeglass and contact lens prescription information; collecting vendor data including product size, product description, product location, price; and recommending vendor products that best match the users' personal data.
1 . A method for product recommendation in a collaborative online environment, the method comprising:
a) receiving, from a user computing device, a personal user data comprising a plurality of user physical characteristics;
b) receiving, from one or more vendor systems, a product metadata corresponding to a plurality of products;
c) generating, by a modeling module, one or more compatibility metrics for the plurality of products, the compatibility metrics indicating a degree of match between the user physical characteristics and the product metadata, wherein the modeling module is configured to generate the compatibility metrics based on features extracted from the personal user data and learned associations between community data and product attributes;
d) selecting at least one product for recommendation based on the compatibility metric exceeding a predefined threshold; and
e) generating, by the modeling module, a three-dimensional visual simulation of a selected product rendered on a user model, wherein the user model is generated from the user physical characteristics, and the three-dimensional visual simulation is generated by deforming a mesh representation of the user model and applying dimensional and texture attributes associated with the selected product onto a deformed mesh to simulate physical appearance.
2 . The method of claim 1 wherein the said user and vendor data are stored for future reference and recommendation.
3 . The method of claim 1 wherein users can shop for and buy products for their friends that are compatible with their friend's personal information including apparel that fits them, without compromising their friend's privacy.
4 . The method of claim 3 wherein a real-time compatibility feedback is communicated to the user computing device, the compatibility feedback comprising at least one of:
a) Flashing arrows or varied color regions and/or other graphic or visual indicator, for instance, to indicate type of fit (tight, loose and other degrees of fit) in a region and where adjustments need to be made for proper fitting;
b) Providing the user with a close up view, zooming onto a specific area of interest on the 3D model to view and examine fit in that region;
c) Using a tape measure animation to indicate the dimensions of a particular body segment or region;
d) Digital effects such as a transparency/x-ray vision effect where the apparel's transparency can be changed in order to enable the user to examine fit in the particular region; and
e) Specifying numeric measurements to indicate fit information including the gap or margin between apparel and body in different regions, after apparel is worn; an overall goodness of fit rating.
5 . The method of claim 3 wherein products that are relevant to the personal user data are shown to the user as the user browses through products including apparel that fits the user, products that matches the user's medical records including eyeglasses or contact lenses that match the user's prescription.
6 . The method of claim 1 in which three-dimensional visual simulation representing the user are generated, comprising:
a) acquisition of multimedia from the user for extraction of data pertaining to physical attributes;
b) controls for dynamically adjusting dimensions of various body parts of the model;
c) use of feedback provided by the user on body information;
d) combining of 2D user images and anthropometric data to construct a 3D body and face model of the user;
e) applying optimization techniques to the generated model to increase precision of match with the user's real face and body;
f) refining the 3D model using texture maps, pattern, color, shape and other information pertaining to the make and material of the apparel to provide photorealism;
g) creating custom looks on the 3D model by selecting apparel, cosmetic, hair and dental products from catalogues or by performing a virtual makeover.
7 . The method of claim 1 , wherein the personal user data comprises at least one of: body measurements, facial imagery, skin tone, motion capture data, demographic information, and stated or inferred style preferences.
8 . The method of claim 1 , wherein the user physical characteristics comprise at least one of: anatomical dimensions, facial structure, and body morphology extracted from the personal user data by feature extraction algorithms.
9 . The method of claim 1 , wherein the product metadata comprises at least one of: product dimensions, fabric or material properties, color information, style category, and product imagery suitable for visual simulation.