Google Inc.

Emilio Rodriguez Antunez, Iii

Wei Zhang

Salih Burak Gokturk

Baris Sumengen

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.

Growing community of inventors

Mountain View, CA, United States of America

Emilio Rodriguez Antunez, Iii