The Community for Technology Leaders
Green Image
<p>A method for estimating 3D displacements from two stereo frames is presented. It is based on the hypothesize-and-verify paradigm used to match 3D line segments between the two frames. In order to reduce the complexity of the method, an assumption is made that objects are rigid. The formulate a set of complete rigidity constraints for 3D line segments and integrate the uncertainty of measurements in this formation. The hypothesize-and-verify stages of the method use an extended Kalman filter to produce estimates of the displacements and of their uncertainty. The algorithm is shown to work on indoor and natural scenes. It is also shown to be easily extended to the case in which several mobile objects are present. The method is quite robust, fast, and has been thoroughly tested on hundreds of real stereo frames.</p>
3D displacement estimation; line segment matching; stereo; hypothesize-and-verify paradigm; complexity; rigidity constraints; extended Kalman filter; image segmentation; Kalman filters; motion estimation; stereo image processing

Z. Zhang and O. Faugeras, "Estimation of Displacements from Two 3-D Frames Obtained From Stereo," in IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 14, no. , pp. 1141-1156, 1992.
89 ms
(Ver 3.3 (11022016))