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Published on: May 7, 2019
Temporal segmentation of video objects for hierarchical object-based motion description
Yue Fu1, Ahmet Ekin, A Murat Tekalp
1Department of Electrical and Computer Engineering, University of Rochester, Rochester, NY 14627-0126, USA.
Abstract:
This paper describes a hierarchical approach for object-based motion description of video in terms of object motions and object-to-object interactions. We present a temporal hierarchy for object motion description, which consists of low-level elementary motion units (EMU) and high-level action units (AU). Likewise, object-to-object interactions are decomposed into a hierarchy of low-level elementary reaction units (ERU) and high-level interaction units (IU). We then propose an algorithm for temporal segmentation of video objects into EMUs, whose dominant motion can be described by a single representative parametric model. The algorithm also computes a representative (dominant) affine model for each EMU. We also provide algorithms for identification of ERUs and for classification of the type of ERUs. Experimental results demonstrate that segmenting the life-span of video objects into EMUS and ERUs facilitates the generation of high-level visual summaries for fast browsing and navigation. At present, the formation of high-level action and interaction units is done interactively. We also provide a set of query-by-example results for low-level EMU retrieval from a database based on similarity of the representative dominant affine models.
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