Extraction technique of region of interest from stereoscopic video  

作　　者：Lu Chaohui Pan Jiaying 

机构地区：[1]School of Information Engineering, Communication University of China, Beijing 100024, China

出　　处：《The Journal of China Universities of Posts and Telecommunications》2017年第5期68-76,共9页中国邮电高校学报（英文版）

基　　金：supported by the National Natural Science Foundation of China (61201236);National Key Technology Support Program (2012BAH01F04);Beijing Key Laboratory of Science and Technology (Z141101004414045)

摘　　要：A feature fusion approach is presented to extract the region of interest （ROI） from the stereoscopic video. Based on human vision system （HVS）, the depth feature, the color feature and the motion feature are chosen as vision features. The algorithm is shown as follows. Firstly, color saliency is calculated on superpixel scale. Color space distribution of the superpixel and the color difference between the superpixel and background pixel are used to describe color saliency and color salient region is detected. Then, the classic visual background extractor （Vibe） algorithm is improved from the update interval and update region of background model. The update interval is adjusted according to the image content. The update region is determined through non-obvious movement region and background point detection. So the motion region of stereoscopic video is extracted using improved Vibe algorithm. The depth salient region is detected by selecting the region with the highest gray value. Finally, three regions are fused into final ROI. Experiment results show that the proposed method can extract ROI from stereoscopic video effectively. In order to further verify the proposed method, stereoscopic video coding application is also carried out on the joint model （JM） encoder with different bit allocation in RO｜ and the background region.A feature fusion approach is presented to extract the region of interest （ROI） from the stereoscopic video. Based on human vision system （HVS）, the depth feature, the color feature and the motion feature are chosen as vision features. The algorithm is shown as follows. Firstly, color saliency is calculated on superpixel scale. Color space distribution of the superpixel and the color difference between the superpixel and background pixel are used to describe color saliency and color salient region is detected. Then, the classic visual background extractor （Vibe） algorithm is improved from the update interval and update region of background model. The update interval is adjusted according to the image content. The update region is determined through non-obvious movement region and background point detection. So the motion region of stereoscopic video is extracted using improved Vibe algorithm. The depth salient region is detected by selecting the region with the highest gray value. Finally, three regions are fused into final ROI. Experiment results show that the proposed method can extract ROI from stereoscopic video effectively. In order to further verify the proposed method, stereoscopic video coding application is also carried out on the joint model （JM） encoder with different bit allocation in RO｜ and the background region.

关 键 词：stereoscopic video DEPTH SALIENCY ROI Vibe 

分 类 号：TN0[电子电信—物理电子学]