Direct Recovery of Three-Dimensional Scene Geometry From Binocular Stereo Disparity
IEEE Transactions on Pattern Analysis and Machine Intelligence
Computer and Robot Vision
Calculating Dense Disparity Maps from Color Stereo Images, an Efficient Implementation
International Journal of Computer Vision
3D Object recognition in cluttered environments by segment-based stereo vision
International Journal of Computer Vision
Advances in Computational Stereo
IEEE Transactions on Pattern Analysis and Machine Intelligence
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There are several strategies of how to retrieve depth information from a sequence of images, like depth from motion, depth from shading and depth from stereopsis. In this paper, we introduce a new method to retrieve depth based on motion and stereopsis. A motion detection representation helps establishing further correspondences between different motion information. This representation bases in the permanency memories mechanism, where jumps of pixels between grey level bands are computed in a matrix of charge accumulators. For each frame of a video stereovision sequence, the method fixes the right permanency stereo memory, and displaces the left permanency stereo memory by pixel on the epipolar restriction basis over the right one, in order to analyze the disparities of the motion trails calculated. By means of this functionality, for all possible displacements of one permanency memory over the other, the correspondences between motion trails are checked, and the disparities are assigned, providing a way to analyze the depths of the objects present in the scene.