Abstract:
A system and method, which may be an offline method, extracts relevant image features about images in a network-based publication system for enabling image similarity searching of such images. An image is uploaded and may be sent to a picture processing service, which generates digests. The digests are compressed data structures each representing a particular image feature such as edge, color, texture, or words. These digests are then stored in a search database, where the digests can be used to retrieve images by image similarity at scale. A similar process can be performed for an image query for searching the search database for images similar to the image.
Abstract:
Image-based features may be significantly correlated with click-through rates of images that depict a product, which may provide a more formal basis for the informal notion that good quality images will result in better click-through rates, as compared to poor quality images. Accordingly, an image assessment machine is configured to analyze image-based features to improve click-through rates for shopping search applications (e.g., a product search engine). Moreover, the image assessment machine may rank search results based on image quality factors and may notify sellers about low quality images. This may have the effect of improving the brand value for an online shopping website and accordingly have a positive long-term impact on the online shopping website.