A9.com, Inc.

Pinkee Rasik Patel Gupta

Aishwarya Natesh

Sharmila Nagaraja Reddy

Andrea Zehr

Andrea Joyce Diane Zehr

Shruthi R Bathina

Whitney Chan

Deborah S Hoo

Sunil Ramesh

William Brendel

Son Dinh Tran

Adam Neustein

Zur Nehushtan

Sean Niu

Shruti Sheorey

Daniya Zamalieva

Shabnam Ghadar

Natasha Duggal

Smita Malaviya

Various embodiments provide for recommending products from an electronic catalog that are aesthetically compatible with an existing item in a physical space based on a live camera view of the space, and rendering augmented reality views of the recommended products into the live camera view. Specifically, an image of the existing item is used to search a database of images of designed spaces that includes a corresponding object visually similar to the existing item. The image of the designed space may also include other items that are visually compatible with the corresponding object and therefore visually compatible with the existing item. Thus, the images of the other items are used to search an electronic catalog for available items that are visually similar to the other items and therefore would be visually compatible with the existing item.

Recommendations based on object detected in an image

A color selection image matching system can receive, from a computing device, image data captured by a camera in the user device, where the image data includes one or more colors. The computing device can extrapolate a subset of the colors and receive an indication of a target color to initiate a product search based on the target color. The subset of colors may be determined based on other image data, and selectable color elements may be generated for the subset of colors. In some embodiments, the system may generate a palette of colors visually similar to the target color. The target color and/or palette of colors can be cross-referenced with products colors, based on standardized or quantitative color descriptors, to determine relevant product search results matching the target color, which may be displayed on the user device.

Color selection for image matching visual search

Disclosed are various embodiments of systems and methods for dynamically generating and providing personalized recommendations of newer products or services potentially of interest to a particular user who has previously purchased a similar product or service. Historical purchase data or other information indicating the user's preferences is analyzed to determine personal preference data. Candidate content is identified based on attributes found in the preference data. Similarity strategies and criteria can be used to test features and qualities in candidate content. Recommended product or service content comes in the form of candidate content which reaches a similarity threshold or otherwise achieves a sufficient confidence score based at least in part on a similarity metric is determined. In accordance with various embodiments, the generation of newer product and service recommendations can be accomplished or optimized by training machine learning models, such as deep neural networks, using preference data for the particular user.

Dynamic recommendations personalized by historical data

Various embodiments provide techniques for generating a style profile in which items are recognized in image data, analyzed for their attributes, and categorized based on those attributes. In various embodiments, computer vision techniques can be used to analyze the image data and subsequent image data to update the generated style profiles. The style profiles may be associated with a person, event, or the like and provide users with items having similar characteristics or attributes, which may be available for purchase in an electronic marketplace. The style profiles may be updated by analyzing user interaction with the provided items and by receiving additional image data. Additionally, recommendations may be provided based on search queries that identify certain events or style profiles.

Computer vision based style profiles

Because not all companies register or obtain barcodes (or other encodings or identifiers) from a single, consistent source, and because different companies can be associated with the same barcode at different times, there can be multiple products associated with a specific barcode. If a user requests information associated with a specific barcode, information associated with the user or request can be used to attempt to determine the associated product if more than one matching product is uncovered. In some embodiments, a location of a user device at approximately a time of the request can be used to attempt to determine the appropriate product, such as if the user is in a store that only offers one of the potential products. Other information can be used as well, such as past locations, purchase history, viewing patterns, and the like.

Barcode disambiguation

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San Mateo, CA, United States of America

Pinkee Rasik Patel Gupta