W4: Real-Time Surveillance of People and Their Activities
IEEE Transactions on Pattern Analysis and Machine Intelligence
Automatic video genre detection for content-based authoring
PCM'04 Proceedings of the 5th Pacific Rim conference on Advances in Multimedia Information Processing - Volume Part I
A complexity-bounded motion estimation algorithm
IEEE Transactions on Image Processing
Performance characterization of video-shot-change detection methods
IEEE Transactions on Circuits and Systems for Video Technology
Shot-boundary detection: unraveled and resolved?
IEEE Transactions on Circuits and Systems for Video Technology
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Low-level video analysis is an important step for further semantic interpretation of the video. This provides information about the camera work, video editing process, shape, texture, color and topology of the objects and the scenes captured by the camera. Here we introduce a framework capable of extracting the information about the shot boundaries and the camera and object motion, based on the analysis of spatiotemporal pixel blocks in a series of video frames. Extracting the motion information and detecting shot boundaries using the same underlying principle is the main contribution of this paper. Besides, this original principle is likely to improve robustness of the abovementioned low-level video analysis as it avoids typical problems of standard frame-based approaches and the camera motion information provides critical help to improve the shot boundary detection performance. The system is evaluated using TRECVID data [1] with promising results.