Systems and methods are provided for automatically generating a thumbnail for a video on an online shopping site. The disclosed technology automatically generates a thumbnail for a video, where the thumbnail represents an item but not necessarily content of the video. A thumbnail generator receives a video that describes the item and an ordered list of item images associated with the item used in an item listing. The thumbnail generator extracts video frames from the video based on sampling rules and determines similarity scores for the sampled video frames. A similarity score indicates a degree of similarity between content of a video frame and an item image. The thumbnail generator determines weighted similarity scores based item images and occurrences of sampled video frames in the video. The disclosed technology generates a thumbnail for the video by selecting a sample video frame based on the weighted similarity scores.

Disclosed herein method and apparatus for simultaneous video retrieval and alignment. According to an embodiment of the present disclosure, there is provided a method for retrieving a video. The method comprising: detecting a section of interest in a query video that is a retrieval request video; producing one or more frame-level descriptor and a video-level descriptors for the query video by using key frames within the detected section of interest; and retrieving a reference video corresponding to the query video based on the frame-level descriptor and the video-level descriptor for the query video and one or more frame-level descriptor and a video-level descriptor for each of reference videos stored in a database.

The present invention relates to a method and a device for determining a duplicate video, wherein the method comprises: acquiring multiple types of video features of a query video; according to the multiple types of video features of the query video, sequentially comparing a plurality of existing videos respectively to obtain a sequence comparison result; performing a first ranking on the plurality of existing videos according to the sequence comparison result, and taking first n existing videos as first candidate videos according to a result of the first ranking, where n is a positive integer; and determining a duplication level of the query video according to the sequence comparison result of the first candidate videos.

A method and apparatus for characteristic-based video processing include: in response to receiving a region of a picture of a video sequence, determining a characteristic in the region, the region being independent of other regions of the picture for video coding; determining a class associated with the region based on the characteristic, the class being selected from a plurality of classes; and encoding the region using a parameter set associated with the class, the parameter set being selected from a plurality of parameter sets for video coding at different quality levels.

Disclosed herein are methods and systems for new analytic pathways for collecting information regarding video playback by human (and automated) users. This is achieved in part by placing certain elements (Vixels) within the code of a video file prior to it being uploaded by a user who shares the video. Whenever and wherever the video is played, whether it is streamed once, downloaded and played several times thereafter, or played for a mass audience, the analytic pathway is triggered each and every time the video file is played because the elements triggering the collection of analytics exist in the video file itself. By embedding Vixels into video files at or before upload, the analytics mechanisms are triggered by the embedded Vixel regardless of how, where, when, and by whom the video is played back, forming the framework for a simpler and more accurate analytics network.

An architecture for a multimedia search system is described. To perform similarity matching of multimedia query frames against reference content, reference database comprising of a cluster index using cluster keys to perform similarity matching and a multimedia index to perform sequence matching is built. Methods to update and maintain the reference database that enables addition and removal of the multimedia contents, including portions of multimedia content, from the reference database in a running system are described. Hierarchical multi-level partitioning methods to organize the reference database are presented. Smart partitioning of the reference multimedia content according to the nature of the multimedia content, and according to the popularity among the social media, that supports scalable fast multimedia identification is also presented. A caching mechanism for multimedia search queries in a centralized or in a decentralized distributed system and a client based local multimedia search system enabling multimedia tracking are described.

Systems and methods for full motion video search are provided. In one aspect, a method includes receiving one or more search terms. The search terms include one or more of a characterization of the amount of man-made features in a video image and a characterization of the amount of natural features in the video image. The method further includes searching a full motion video database based on the one or more search terms.

A system and method for generating personalized multimedia content element clusters. The method includes determining, based on at least one interest, at least one personalized concept, wherein each personalized concept represents one of the at least one user interest; obtaining at least one multimedia content element related to a user; generating at least one signature for the at least one multimedia content element, each generated signature representing at least a portion of the at least one multimedia content element; determining, based on the generated at least one signature, at least one multimedia content element cluster, wherein each cluster includes a plurality of multimedia content elements sharing a common concept of the at least one personalized concept; and creating at least one personalized multimedia content element cluster by adding, to each determined cluster, at least one of the at least one multimedia content element sharing the common concept of the cluster.

Systems and methods for full motion video search are provided. In one aspect, a method includes receiving one or more search terms. The search terms include one or more of a characterization of the amount of man-made features in a video image and a characterization of the amount of natural features in the video image. The method further includes searching a full motion video database based on the one or more search terms.

The overall architecture and details of a scalable video fingerprinting and identification system that is robust with respect to many classes of video distortions is described. In this system, a fingerprint for a piece of multimedia content is composed of a number of compact signatures, along with traversal hash signatures and associated metadata. Numerical descriptors are generated for features found in a multimedia clip, signatures are generated from these descriptors, and a reference signature database is constructed from these signatures. Query signatures are also generated for a query multimedia clip. These query signatures are searched against the reference database using a fast similarity search procedure, to produce a candidate list of matching signatures. This candidate list is further analyzed to find the most likely reference matches. Signature correlation is performed between the likely reference matches and the query clip to improve detection accuracy.