3-D surface description from binocular stereo

Fuzzy Control System to Solve Coupling Between Tracking and Predictive Algorithms

“…Stereo vision is a part of the field of computer vision that uses two or more cameras to obtain two or more images from which distance information can be obtained by using the triangulation principle (Cochran & Medioni, 1992). We can obtain three-dimensional information of static scenes by using this technique.…”

Fast Computation of Dense and Reliable Depth Maps from Stereo Images

“…A similar approach named the No Isolated Pixel Constraint Cochran & Medioni (1992) identifies disparity values as isolated if its difference is bigger than 2.5 px according to the average of a 5 x 5 px-block. This method is evaluated subsequently using a block size of 3 x 3 px.…”

“…While counting the number of valid pixels in their neighborhood it can be easily estimated whether the pixel is isolated or not. Thus in the implementation a pixel identifies as isolated if the number of valid pixels in its neighborhood is less than two, following Cochran & Medioni (1992 The effect of different sized correlation blocks is described in section 3.3 whereas small block sizes are good for fine details yet sensitive to noise, while big block sizes create a smooth depth map by blurring edges and details. Due to their size big blocks contain more information and have a greater probability for being unique.…”

A Matlab-Based Testbed for Integration, Evaluation and Comparison of Heterogeneous Stereo Vision Matching Algorithms

“…According to [1] and [2], the classical problem of stereo analysis consist mainly of the following steps: image acquisition, camera modelling, feature extraction, image matching and depth determination. Of these, the matching process-the process of identifying features in both images and searching for correspondences-is the key step.…”