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13 September 2008 Mobile video processing for visual saliency map determination
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Abstract
The visual saliency map represents the most attractive regions in video. Automatic saliency map determination is important in mobile video applications such as autofocusing in video capturing. It is well known that motion plays a critical role in visual attention modeling. Motion in video consists of camera's motion and foreground target's motion. In determining the visual saliency map, we are concerned with the foreground target's motion. To achieve this, we evaluate the camera/global motion and then identify the moving target from the background. Specifically, we propose a three-step procedure for visual saliency map computation: 1) motion vector (MV) field filtering, 2) background extraction and 3) contrast map computation. In the first step, the mean value of the MV field is treated as the camera's motion. As a result, the MV of the background can be detected and eliminated, and the saliency map can be roughly determined. In the second step, we further remove noisy image blocks in the background and provide a refined description of the saliency map. In the third step, a contrast map is computed and integrated with the result of foreground extraction. All computations required in the our proposed algorithm are low so that they can be used in mobile devices. The accuracy and robustness of the proposed algorithm is supported by experimental results.
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Shilin Xu, Weisi Lin, and C.-C. Jay Kuo "Mobile video processing for visual saliency map determination", Proc. SPIE 7073, Applications of Digital Image Processing XXXI, 70730O (13 September 2008); https://doi.org/10.1117/12.796753
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