Live inventory management environment system and methods are disclosed. A shelf for items has bins each with an associated sensor. A processor receives a detection signal from the sensor which indicates placement or removal an item(s) from an associated bin. An entry device sends an entered request for placement or removal of items to the processor, and an indicator strip has lights which uniquely identify each one of the bins when lit. The processor has information relating to which bin each subset of lights is associated, and causes activation of a subset of lights associated with a bin of the item(s) in the request and records in memory a type of action, a time stamp and a quantity of the item(s) placed or removed from the bin having the subset of lights lit and indicated in the detection signal subsequently received from the sensor of the associated bin.

The invention presents an example-based real-time clothing synthesis method, which includes the following steps: creating the 3D human model according to the input body pose parameters and the body shape parameters; generating 3D clothing deformation on the standard shape and the input pose through a clothing pose model; searching nearby clothing shape models according to the body pose parameters; for each nearby clothing shape model, generating corresponding 3D clothing mesh based on the body shape parameters, and then deforming the clothing mesh toward the input pose using Linear Blend Skinning (LBS) method; synthesizing the clothing deformation for the input body pose and shape using the clothing data obtained in above steps; resolving the interpenetrations between the clothing data and the human model. The invention can generate real-time clothing animation results with detailed wrinkles for various body poses and shapes with different clothing types on a commodity CPU, without resizing the cloth model. It has potential use in assessment of fitness in virtual try-on, as well as in the field of computer animation and video games.

Fingerprinting physical items to mint NFTs is described. One or more features of a physical item are captured using a fingerprint capture system of a client device, and a fingerprint of the physical item is generated using the captured features of the physical item. The fingerprint of the physical item is provided to an authentication service to verify that the physical item corresponds to an authentic physical item by matching the fingerprint of the physical item to distinguishing features of the authentic physical item. Responsive to verification by the authentication service, a digital twin NFT is minted on a blockchain using the matched fingerprint. A combined listing for the physical item and the digital twin NET is then generated on a listing platform.

An individual article management apparatus (2000) acquires product identification information (10) about a target product and preference information (30) about a user. The individual article management apparatus (2000) generates output information (40), based on the acquired preference information (30) and attribute information about each individual article of a target product determined by the acquired product identification information (10). The output information (40) associated with a product includes a captured image related to one or more individual articles of the product. The individual article management apparatus (2000) determines one or more individual articles having attribute information associated with the acquired preference information from among a plurality of individual articles of a product determined by the acquired identification information, and generates the output information including a captured image related to the determined individual article.

An online concierge system includes sponsored content items in an interface including different slots for displaying content items. A sponsored content item may be displayed in a single slot or in multiple adjacent slots. The online concierge system determines a content score for various sponsored content items indicating a likelihood of a user interacting with a sponsored content item and a position bias for slots in the interface indicating a likelihood of the user interacting with a slot independent of content in the slot. Position biases are different dependent on a number of slots in which a content item is displayed. The online concierge system generates a graph identifying potential placements of sponsored content items in slots by selecting content items in an order according to their content scores. Sponsored content items are positioned in slots according to a path through the graph that has the highest overall expected value.

A system and a method are disclosed for a platform that determines the classification of a physical asset received from a provider. For a physical asset, the platform extracts intrinsic data from the asset and compiles extrinsic data by web scraping data associated with the asset. The platform generates a principal component vector comprising the intrinsic data and extrinsic data and inputs the principal component vector into a machine learning model. The machine-learning model is trained using training data that includes an aggregation of principal components of a physical asset as labeled by a historical classification and a time associated with the entry. The machine-learning model outputs the classification of the physical asset corresponding to a present time. The platform provides the classification to a user in visual association with a representation of the physical asset.

Systems and methods for automating clothing transactions. The methods comprise: obtaining user input data and/or sensor data specifying characteristics of a body for an individual; transforming the user input data and/or sensor data into a 3D graphical representation of the body; analyzing the 3D graphical representation to derive 3D body measurements for the individual; identifying clothing items based on results from comparing the 3D body measurements to reference measurements associated with clothing items having different styles, sizes and brand associations; analyzing how a fabric elasticity and a garment construction could impact a fit of each identified clothing item relative to each body part of the individual based on the 3D graphical representation of the body; and filtering the clothing items based on results of the analyzing and fit preferences of the individual to generate recommended clothing items for the individual.

The present disclosure presents systems and methods that provide personalized information to help individuals optimize the contents their wardrobe in a dynamic manner. The digital wardrobe application can enhance consumers' experience and decision process around what to buy, wear, and sell by proposing a digital wardrobe that can provide information on 1) the number of incremental outfits the user could build with a new given item of clothing, 2) the usage rates of the a garment, 3) the resale value of the item of clothing, 4) the environmental impact of the clothing, and 5) the ability to connect the digital wardrobe across third parties. Through such information, individuals can be better able to optimize the clothes that they buy and own while maximizing the value and environmental impact of the entirety of their wardrobes (thereby reducing overall spend and waste).

A method of operating a server for products customization service according to an embodiment of the present invention includes providing product options providable to a purchaser, providing image information of a product selected by the purchaser among the product options, providing design options addable to the product, reflecting a design option selected by the purchaser among the design options to the image information of the product, and providing the image information of the product to which the design option selected by the purchaser is reflected.

The disclosure is directed at a method for data collection and processing within an online system which monitors a user's activity on the online system and then creates a list of business offers for display to the user. The list of business offers is not displayed to the user until the user performs an action relating to a request to review the list of business offers.