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Consistent Depth Maps Estimation from Binocular Stereo Video Sequence
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作者 段峰峰 《Journal of Shanghai Jiaotong university(Science)》 EI 2016年第2期184-191,共8页
In the paper, an approach is proposed for the problem of consistency in depth maps estimation from binocular stereo video sequence. The consistent method includes temporal consistency and spatial consistency to elimin... In the paper, an approach is proposed for the problem of consistency in depth maps estimation from binocular stereo video sequence. The consistent method includes temporal consistency and spatial consistency to eliminate the flickering artifacts and smooth inaccuracy in depth recovery. So the improved global stereo matching based on graph cut and energy optimization is implemented. In temporal domain, the penalty function with coherence factor is introduced for temporal consistency, and the factor is determined by Lucas-Kanade optical flow weighted histogram similarity constraint(LKWHSC). In spatial domain, the joint bilateral truncated absolute difference(JBTAD) is proposed for segmentation smoothing. The method can smooth naturally and uniformly in low-gradient region and avoid over-smoothing as well as keep edge sharpness in high-gradient discontinuities to realize spatial consistency. The experimental results show that the algorithm can obtain better spatial and temporal consistent depth maps compared with the existing algorithms. 展开更多
关键词 consistent depth maps binocular stereo video sequence Lucas-Kanade optical flow weighted histogram similarity constraint(LKWHSC) joint bilateral truncated absolute difference(JBTAD)
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Ship detection in optical remote sensing image based on visual saliency and AdaBoost classifier 被引量:10
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作者 王慧利 朱明 +1 位作者 蔺春波 陈典兵 《Optoelectronics Letters》 EI 2017年第2期151-155,共5页
In this paper, firstly, target candidate regions are extracted by combining maximum symmetric surround saliency detection algorithm with a cellular automata dynamic evolution model. Secondly, an eigenvector independen... In this paper, firstly, target candidate regions are extracted by combining maximum symmetric surround saliency detection algorithm with a cellular automata dynamic evolution model. Secondly, an eigenvector independent of the ship target size is constructed by combining the shape feature with ship histogram of oriented gradient(S-HOG) feature, and the target can be recognized by Ada Boost classifier. As demonstrated in our experiments, the proposed method with the detection accuracy of over 96% outperforms the state-of-the-art method. efficiency switch and modulation. 展开更多
关键词 classifier AdaBoost histogram automata symmetric pixel candidate similarity surround segmentation
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