Several new algorithms for visual correspondence based on graph cuts [7, 14, 17] have recently been developed. While these methods give very strong results in practice, they do not handle occlusions properly. Specifically, they treat the two input images asymmetrically, and they do not ensure that a pixel corresponds to at most one pixel in the other image. In this paper, we present a new method which properly addresses occlusions, while preserving the advantages of graph cut algorithms. We give experimental results for stereo as well as motion, which demonstrate that our method performs well both at detecting occlusions and computing disparities.

Abstract. We present a new bio-inspired approach applied to a problem of stereo images matching. This approach is based on an artifical epidemic process, that we call “the infection algorithm. ” The problem at hand is a basic one in computer vision for 3D scene reconstruction. It has many complex aspects and is known as an extremely difficult one. The aim is to match the contents of two images in order to obtain 3D informations which allow the generation of simulated projections from a viewpoint that is different from the ones of the initial photographs. This process is known as view synthesis. The algorithm we propose exploits the image contents in order to only produce the necessary 3D depth information, while saving computational time. It is based on a set of distributed rules, that propagate like an artificial epidemy over the images. Experiments on a pair of real images are presented, and realistic reprojected images have been generated. 1

This thesis proposal addresses the stereoscopic matching. An introduction to the correspondence problem is given at the beginning. Then, State-of-the-Art in the field of binocular stereo matching is presented. Our previous research focusing this problem is described together with its classification among recent stereo matching approaches. Finally, the thesis goals are formulated.

Predictive displays have proven their suitability to compensate time delays in the visual feedback of teleoperation applications. Using camera images for texture mapping and a geometric model of the remote scene photo-realistic predictions can be achieved. The aim of the presented work is the acquisition and update of a geometric scene model of the remote scene using camera images. A hierarchical structure of the model is described, that facilitates the transformation of 3D point clouds to a polygon-based description for computer graphics. In addition to the concepts, some experimental results in scene reconstruction are presented.

Abstract – In this paper, we present a cooperative stereo vision algorithm with three cameras for dense disparity mapping and occlusion detection. Based on nonlinear iteration and multiple cameras, the disparity maps are smooth and the object boundaries are accurate. Occlusions for each stereo pair are detected effectively by examining the iterative inhibition and magnification of the matching evaluation.

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In this paper, a detailed experimental study of occlusion detection in the controlled environmentsbased on skin color is proposed.The image is given as an input to the face detection algorithm to detect the faces. Some faces are not detected dueto occlusion, so an occlusion detection technique is implemented to detect all the occluded faces. Those occlusions are detected using skin color of the faces. This is implemented by using circular Hough transform through plotting of circles on the faces present in the image. In order to overcome the illumination problem, extraction of local SMQT features is done. After completion of face detection, occlusions are detected based on skin color and the respective spatial locations of the image are returned.To differentiate the skin colors with other colors, SVM classifier is used. Huge datasets are collected for the purpose of training.From the image database, the occluded faces are recognized by retrieving it through spatial location. This implementation is suitable for all face detection applications in constrained environments the experiment using this technique havegiven