Hierarchical Representation of Videos with Spatio-Temporal Fibers

Ratnesh Kumar 1 Guillaume Charpiat 1 Monique Thonnat 1
1 STARS - Spatio-Temporal Activity Recognition Systems
CRISAM - Inria Sophia Antipolis - Méditerranée
Abstract : We propose a new representation of videos, as spatio- temporal fibers. These fibers are clusters of trajectories that are meshed spatially in the image domain. They form a hier- archical partition of the video into regions that are coherent in time and space. They can be seen as dense, spatially- organized, long-term optical flow. Their robustness to noise and ambiguities is ensured by taking into account the relia- bility of each source of information. As fibers allow users to handle easily moving objects in videos, they prove useful for video editing, as demonstrated in a video inpainting example.
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Ratnesh Kumar, Guillaume Charpiat, Monique Thonnat. Hierarchical Representation of Videos with Spatio-Temporal Fibers. IEEE Winter Conference on Applications of Computer Vision, Mar 2014, Colorado, United States. ⟨hal-00911012⟩

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