Video segmentation based on detected video features using a graphical model

Abstract

Embodiments are directed to video segmentation based on detected video features. More specifically, a segmentation of a video is computed by determining candidate boundaries from detected feature boundaries from one or more feature tracks; modeling different segmentation options by constructing a graph with nodes that represent candidate boundaries, edges that represent candidate segments, and edge weights that represent cut costs; and computing the video segmentation by solving a shortest path problem to find the path through the edges (segmentation) that minimizes the sum of edge weights along the path (cut costs). A representation of the video segmentation is presented, for example, using interactive tiles or a video timeline that represent(s) the video segments in the segmentation.

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