Emerging Topics in Computer Vision

3.9. Dense Depth Estimation

With the camera calibration given for all viewpoints of the sequence, we can proceed with methods developed for calibrated structure from motion algorithms. The feature tracking algorithm already delivers a sparse surface model based on distinct feature points. This, however, is not sufficient to reconstruct geometrically correct and visually pleasing surface models. This task is accomplished by a dense disparity matching that estimates correspondences from the gray level images directly by exploiting additional geometrical constraints. The dense surface estimation is done in a number of steps. First, image pairs are rectified to the standard stereo configuration. Then, disparity maps are computed through a stereo ...