EMS: Energy Minimization Based Video Scene Segmentation
Zhiwei Gu
Tao Mei
Xian-Sheng Hua
Xiuqing Wu
Shipeng Li
Univ. of Sci. & Technol. of China, Hefei;
This paper appears in: Multimedia and Expo, 2007 IEEE International Conference on
Publication Date: 2-5 July 2007
On page(s): 520-523
Location: Beijing,
ISBN: 1-4244-1016-9
INSPEC Accession Number: 9804344
Digital Object Identifier: 10.1109/ICME.2007.4284701
Current Version Published: 2007-08-08
Abstract
This paper proposes a novel energy minimization based approach to video scene segmentation. In video content analysis, scene is defined as a set of adjacent shots related to a particular setting or a continuous action in one place. This indicates that not only the global distribution of time and content, but also the local temporal continuity should be taken into account for scene segmentation. Motivated from this fact, we formulate the segmentation procedure as a unified energy minimization framework, in which the global and local constraint is represented by content and context energy, respectively. This energy minimization problem is optimized by two steps in an iterative fashion: first find an initial estimation of scene label for content energy by a generative model; and then iterated conditional modes (ICM) is used for context energy to find the global optimization. Furthermore, a boundary voting procedure is devised to decide the optimal scene boundaries. We apply EMS on an extensive set of home videos and feature movies, and report superior performance compared with several existing key approaches to scene segmentation.
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