Abstract:
A system and method, which may be an offline method, extracts relevant image features about listing items in a network-based publication system for enabling image similarity searching of such listing items. When a seller lists an item, an image of the item is uploaded and may be sent to a picture processing service, which generates several 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 listings by image similarity at scale. A similar process can be performed for a query listing for searching the search database for items similar to the query listing.
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 query image.
Abstract:
A system and method, which may be an offline method, extracts relevant image features about listing items in a network-based publication system for enabling image similarity searching of such listing items. When a seller lists an item, an image of the item is uploaded and may be sent to a picture processing service, which generates several 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 listings by image similarity at scale. A similar process can be performed for a query listing for searching the search database for items similar to the query listing.
Abstract:
A system and method, which may be an offline method, extracts relevant image features about listing items in a network-based publication system for enabling image similarity searching of such listing items. When a seller lists an item, an image of the item is uploaded and may be sent to a picture processing service, which generates several 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 listings by image similarity at scale. A similar process can be performed for a query listing for searching the search database for items similar to the query listing.
Abstract:
A system and method, which may be an offline method, extracts relevant image features about listing items in a network-based publication system for enabling image similarity searching of such listing items. When a seller lists an item, an image of the item is uploaded and may be sent to a picture processing service, which generates several 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 listings by image similarity at scale. A similar process can be performed for a query listing for searching the search database for items similar to the query listing.
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:
A system and method extracts relevant image features about listed products in a network-based publication system for enabling image similarity searching of such listed products. When a seller lists a product, an image of the product is uploaded and may be sent to a picture processing service, which generates several digests. The digests are compressed data structures each representing a particular image feature of a listed product such as edge, color, texture, or words. These digests are then stored in a database, where the digests can be used to retrieve listings of products by image similarity at scale. A similar process can be performed for a query by image similarity searching the database for products similar to the query. When a product is located by image similarity search, a selectable icon is provided to enable more products like the located product to be located by image similarity search.
Abstract:
A system and method, which may be an offline method, extracts relevant image features about listing items in a network-based publication system for enabling image similarity searching of such listing items. When a seller lists an item, an image of the item is uploaded and may be sent to a picture processing service, which generates several 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 listings by image similarity at scale. A similar process can be performed for a query listing for searching the search database for items similar to the query listing.
Abstract:
A first database search is performed for images similar to a first query image, and a first plurality of images that result from the first database search are provided. The first plurality of images are selectable to provide a second query image. A second database search is performed for images similar to the second query image, and a second plurality of images that result from the second search are provided. The second plurality of images are selectable to provide a third query image. A third database search is performed for images similar to the third query image; and a third plurality of images that result from the third database search are provided. The third plurality of images are selectable for providing a fourth query image. The search can continue to additional depths. Similarity may be determined by pixel color gradients using windows of computation.