We present a novel robust methodology for corresponding a dense set of points on an object surface from photometric values, for 3-D stereo computation of depth. We use two stereo p...
Depth estimation in computer vision and robotics is most commonly done via stereo vision (stereopsis), in which images from two cameras are used to triangulate and estimate distan...
We introduce a generic structure-from-motion approach based on a previously introduced, highly general imaging model, where cameras are modeled as possibly unconstrained sets of p...
Srikumar Ramalingam, Suresh K. Lodha, Peter F. Stu...
Stereo matching commonly requires rectified images that
are computed from calibrated cameras. Since all under-
lying parametric camera models are only approximations,
calibratio...
Stereo matching algorithms conventionally match over a range of disparities sufficient to encompass all visible 3D scene points. Human vision however does not do this. It works ov...