Google Inc.

Like.com

Baris Sumengen

Salih Burak Gokturk

Dragomir Dimitrov Anguelov

Vincent Olivier Vanhoucke

Munjal Shah

Xiaofan Lin

Azhar H Khan

Diem Thanh Vu

Navneet Dalal

Danny Yang

Lorenzo Torresani

Wei Zhang

Emilio Rodriguez Antunez, Iii

A system includes an image analysis module that is configured to programmatically analyze individual images in a collection of images in order to determine information about each image in the collection. The system may also include a manual interface that is configured to (i) interface with one or more human editors, and (ii) displays a plurality of panels concurrently. Individual panels may be provided for one or more analyzed images, and individual panels may be configured to display information that is at least indicative of the one or more images of that panel and/or of the information determined from the one or more images.

System and method for enabling image searching using manual enrichment, classification, and/or segmentation

Embodiments enable searching of portions of objects in images, including programmatically analyzing each image in a collection in order to determine image data that, for individual images in the collection, represents one or more visual characteristics of a portion of an object shown in that image. A user is enabled to specify one or more search criteria that includes image data, and a search result may be determined based on one or more images in the collection that show a corresponding object that has a portion that satisfies a threshold. The threshold is defined at least in part by the one or more search criteria.

System and method for search portions of objects in images and features thereof

A set of silhouette attributes are determined for a class of objects, where each of the silhouette attribute corresponds to a discriminative feature that is not associated with any other silhouette attribute in the set. An image content item depicting an object of the class is analyzed. A discriminative feature is identified for the object. The silhouette attribute associated with the determined discriminative feature is associated with the object as provided in the image content item.

Programmatic silhouette attribute determination

Product data for a product is received by an attribute selection module. The product data includes product image data and product text data. This product data is used to generate a plurality of probability distributions for a category. The category includes a plurality of attributes, and the probability distribution includes a plurality of probabilities indicating the likelihoods that attributes of the category are applicable to the product. The plurality of probability distributions for the category are weighted and summed to generate a combined probability distribution for the category. An attribute label is determined by selecting an attribute from the category that is indicated to be most likely applicable to the product based on the combined probability distribution for the category. The attribute label is associated with the product. The attribute label enables other services to search for and retrieve the product based on the attribute.

Automated product attribute selection

Embodiments described herein provide a system and method for providing merchandise items at a network site. According to an embodiment, an image of a merchandise item is obtained. The image is programmatically analyzed to determine information about the merchandise item. The information is used to generate a presentation that includes the merchandise item.

System and method for using image analysis and search in E-commerce

Embodiments described herein provide for a system for creating a data collection of recognized images. The system includes an image analysis module that is configured to programmatically analyze individual images in a collection of images in order to determine information about each image in the collection. The system may also include a manual interface that is configured to (i) interface with one or more human editors, and (ii) displays a plurality of panels concurrently. Individual panels may be provided for one or more analyzed images, and individual panels may be configured to display information that is at least indicative of the one or more images of that panel and/or of the information determined from the one or more images. Additionally, the manual interface enables the one or more human editors to view the plurality of panels concurrently and to interact with each of the plurality of panels in order to correct or remove any information that is incorrectly determined from the image of that panel.

Embodiments programmatically analyze each of a plurality of images in order to determine one or more visual characteristics about an item shown in each of the plurality of images. Data is stored corresponding to the one or more visual characteristics. An interface in is provided for which a user is able to specify one or more search criteria. In response to receiving the one or more search criteria, a search operation is performed to identify one or more items that have a visual characteristic that satisfies at least some of the one or more search criteria.

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San Francisco, CA, United States of America

Baris Sumengen