Content-preserving zoom-in view generation for surveillance videos

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There are several zoom-in video display methods including full-zoom and fisheye view that magnify the regions of interest (ROIs). However, those methods usually discard or deform the remaining regions without considering their content. In this paper, we propose a method for generating a content-preserving zoom-in view which magnifies ROIs and at the same time preserves the content of the remaining regions. Targeting on surveillance videos, our method firstly extracts moving objects from every input frame as ROIs. Then, the importance score is calculated for each pixel in the input frame based on its content to determine where the deformation, which may cause the destruction of the content, should be avoided. Finally, a mapping problem from the input frame to the zoom-in view with respect to the importance score is formulated to deform less important regions more than the important ones. Experiments are conducted to study the effectiveness of considering the content importance. We also compare the results of our method with those of other methods, fisheye view and a method of using uniform scaling and seam carving.

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