Visual reconstruction of ground plane obstacles in a sparse view robot environment
Graphical Models - Special issue on SPM 05
Joint optical flow estimation, segmentation, and 3D interpretation with level sets
Computer Vision and Image Understanding
IEEE Transactions on Pattern Analysis and Machine Intelligence
A variational method for the recovery of dense 3D structure from motion
Robotics and Autonomous Systems
Over-Parameterized Variational Optical Flow
International Journal of Computer Vision
Fast 3-D interpretation from monocular image sequences on large motion fields
ACCV'07 Proceedings of the 8th Asian conference on Computer vision - Volume Part II
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The purpose of this study is to investigate a new method for recovering relative depth and 3D motion from a temporal sequence of monocular images. The method is direct insomuch as it does not require computation of image motion prior to 3D interpretation. This interpretation is obtained by minimizing a functional with two characteristic terms, one of conformity to the spatiotemporal changes in the image sequence, the other of regularization based on anisotropic diffusion. The Euler-Lagrange equations corresponding to the functional minimization are solved iteratively via the half-quadratic algorithm.