Abstract: Systems and methods for analyzing trends in image data is disclosed. A trend query is received relating to an object category and defining two or more groups of interest for which trend data is to be determined with a defined time period. Visual tokens of interest are identified relating to the object category for use in searching a token database. One or more image data sets are identified that are associated with each of the two or more groups of interest. Visual tokens are analyzed matching the visual tokens of interest that are associated with the identified image data sets to generate trend data for each of the two or more groups of interest for the defined period of time. An output is generated based on a comparison of the trend data generated for the two or more groups of interest for the defined period of time.

Abstract: Systems and methods for identifying trends in image data using image classification is disclosed. An image is processed to detect an object in the image by performing foreground detection on the image. The object is classified in accordance with an object category, and one or more attributes of the object are determined. A visual token is generated that comprises information including the object category and the one or more attributes of the object. A trend is identified in at least one of the object and an attribute of the object by analyzing a database storing a plurality of visual tokens.

Abstract: Systems and methods for analyzing trends in image data is disclosed. A trend query is received relating to an object category and defining two or more groups of interest for which trend data is to be determined with a defined time period. Visual tokens of interest are identified relating to the object category for use in searching a token database. One or more image data sets are identified that are associated with each of the two or more groups of interest. Visual tokens are analyzed matching the visual tokens of interest that are associated with the identified image data sets to generate trend data for each of the two or more groups of interest for the defined period of time. An output is generated based on a comparison of the trend data generated for the two or more groups of interest for the defined period of time.

Abstract: Systems and methods for identifying trends in image data using image classification is disclosed. An image is processed to detect an object in the image by performing foreground detection on the image. The object is classified in accordance with an object category, and one or more attributes of the object are determined. A visual token is generated that comprises information including the object category and the one or more attributes of the object. A trend is identified in at least one of the object and an attribute of the object by analyzing a database storing a plurality of visual tokens.

Abstract: A method for resolving out of stock products in online shopping using image classification is disclosed. Product images are processed to determine feature descriptors to generate object classifiers to associated image similarities. A product is determined to be unavailable from a retailer. The product identifier is then provided to a hierarchical database containing indexed product images to determine therefrom other products whose images have classified similarities to images of the product. Similar products can then be presented to the user based upon their visual characteristics providing an improved product correlation.

Abstract: An electronic image classification and search system and method are provided. Images are processed to determine a plurality of simple feature descriptors based upon characteristics of the image itself. The simple feature descriptors are grouped into complex features based upon the orientation of the simple feature descriptors. End-stopped complex feature descriptors and complex feature descriptors at multiple orientations are grouped into hypercomplex feature descriptors. Hypercomplex resonant feature descriptor clusters are generated by linking pairs of hypercomplex feature descriptors. Feature hierarchy classification can then be performed by adaptive resonance on feature descriptors and classifier metadata associated with the image can then be generated to facilitate indexing and searching of the image within a hierarchical image database.

Abstract: An electronic image classification and search system and method are provided. Images are processed to determine a plurality of simple feature descriptors based upon characteristics of the image itself. The simple feature descriptors are grouped into complex features based upon the orientation of the simple feature descriptors. End-stopped complex feature descriptors and complex feature descriptors at multiple orientations are grouped into hypercomplex feature descriptors. Hypercomplex resonant feature descriptor clusters are generated by linking pairs of hypercomplex feature descriptors. Feature hierarchy classification can then be performed by adaptive resonance on feature descriptors and classifier metadata associated with the image can then be generated to facilitate indexing and searching of the image within a hierarchical image database.