International Business Machines Corporation

Yevgeny Burshtein

Daniel Nechemia Rotman

Dror Porat

Peter Bak

Gal Ashour

Udi Barzelay

Tal Hakim

An example system includes a processor to receive a number of videos. The processor is to generate a number of image clouds based on the videos. The processor is to present an interactive image cloud representation including the image clouds. Each image cloud includes a representative image and a number of associated images.

Interactive image cloud visualization of videos

Embodiments may provide techniques that provide identification of images that can provide reduced resource utilization due to reduced sampling of video frames for visual recognition. For example, in an embodiment, a method of visual recognition processing may be implemented in a computer system comprising a processor, memory accessible by the processor, and computer program instructions stored in the memory and executable by the processor, the method comprising: coarsely segmenting video frames of video stream into a plurality of clusters based on scenes of the video stream, sampling a plurality of video frames from each cluster; determining a quality of each cluster, re-clustering the video frames of video stream to improve the quality of at least some of the clusters.

System and method for reducing resources costs in visual recognition of video based on static scene summary

A system comprising a non-transient computer-readable storage medium having stored thereon instructions and at least one hardware processor configured to execute the instructions, to receive a video sequence; divide the video sequence into one or more scenes based on scene boundaries, wherein each scene comprises a plurality of temporally-contiguous image frames, and wherein said scene boundaries are being determined based on a similarity metric between two temporally-contiguous image frames meeting a dissimilarity threshold; and, for each scene of the one or more scenes, (i) generate a plurality of preliminary classifications of an object appearing in at least some of said image frames in the scene, wherein each of said plurality of preliminary classifications has a confidence score, and (ii) calculate a combined classification of the object based on said plurality of preliminary classifications, wherein each of said preliminary classifications is weighted in accordance with its confidence score.

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Nesher, Israel

Yevgeny Burshtein