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ABSTRACT: In this paper we propose a method that smartly improves occlusion handling in stereo matching using trinocular stereo. The main idea is based on the assumption that any occluded region in a matched stereo pair (middle-left images) in general is not occluded in the opposite matched pair (middle-right images). Then two disparity space images (DSI) are merged in one composite DSI. The proposed integration differs from the known approach that uses a cumulative cost. The experimental results are evaluated on the Middlebury data set, showing high performance of the proposed algorithm especially in the occluded regions. Our method solves the problem on the base of a real matching cost, in such a way a global optimization problem is solved just once, and the resultant solution does not have to be corrected in the occluded regions. In contrast, the traditional methods that use two images approach have to complicate a lot their algorithms by additional add hog or heuristic techniques to reach competitive results in occluded regions.
Image Processing (ICIP), 2009 16th IEEE International Conference on; 12/2009
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ABSTRACT: This paper presents an efficient real-time method for detecting moving objects in unconstrained environments, using a background subtraction technique. A new background model that combines spatial and temporal information based on similarity measure in angles and intensity between two color vectors is introduced. The comparison is done in RGB color space. A new feature based on chromaticity and intensity pattern is extracted in order to improve the accuracy in the ambiguity region where there is a strong similarity between background and foreground and to cope with cast shadows. The effectiveness of the proposed method is demonstrated in the experimental results and comparison with others approaches is also shown.
Pattern Recognition, 2008. ICPR 2008. 19th International Conference on; 01/2009
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ABSTRACT: Face detection and tracking, through image sequences, are primary steps in many applications such as video surveillance, human computer interface, and expression analysis. Many currently existing techniques donpsilat perform well due to pose variations, appearance changes, illumination changes, complex backgrounds, and inaccurate initialization. The last short coming, which is the difficulty to initialize motion regions, is a problem facing any tracker. In this paper, we present an automatic and robust face detection and tracking system for color image sequences. Face detection is done using skin color segmentation and connected components analysis. Later, facial features are detected by active shape models and a face mesh is initialized. Finally, the tracking is done by active appearance models. Experimental detection and tracking results on a pose varying face video are given.
Pattern Recognition, 2008. ICPR 2008. 19th International Conference on; 01/2009
