23 December 1997 Automatic dominant camera motion annotation for video retrieval
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An efficient method is derived to classify the dominant camera motions in video shots. Various 3-D camera motions including camera pan, tilt, zoom, Z-rotation, and translations are detected. The method is to analyze the optical flow in a decomposed manner. Images are divided into some sub-regions according to our camera model. The projected x and y components of optical flow are analyzed separately in the different sub-regions of the images. Different camera motions are recognized by comparing the computed result with the prior known patterns. The optical flow is computed by using the Lucas-Kanade method, which is quite efficient due to non- iteration computation. Our method is efficient and effective because only some mean values and standard deviations are used. The analysis and detailed description of our method is given in this paper. Experimental results are presented to show the effectiveness of our method.
© (1997) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Wei Xiong, John Chung-Mong Lee, "Automatic dominant camera motion annotation for video retrieval", Proc. SPIE 3312, Storage and Retrieval for Image and Video Databases VI, (23 December 1997); doi: 10.1117/12.298469; https://doi.org/10.1117/12.298469

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