Proceedings of the International Conference on Information Engineering and Applications (IEA) 2012 pp 675-682 | Cite as
Research on Video Abstraction
Abstract
This paper focuses on designing a system that is capable of abstracting useful video frames for archiving, cataloging, indexing, and editing purpose. Among the different features of video frames, statistics histogram is adopted to detect key frames because of its low sensitivity toward motion, low complexity of calculation, and robustness to noise. In addition, cumulative histogram is adopted to detect the edges of video frames due to its lower sensitivity to the motion of objects/camera and illumination variations than statistics histogram. Dynamic threshold-based sliding window is used to detect the shot boundaries and efficiently get the key frames in favor of its representativeness.
Keywords
Video abstraction Histogram Shot boundary detection Key frameReferences
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