Estimating the Kinematics and Structure of a Rigid Object from a Sequence of Monocular Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Shape and motion from image streams under orthography: a factorization method
International Journal of Computer Vision
Introduction: a Bayesian formulation of visual perception
Perception as Bayesian inference
Artificial Vision for Mobile Robots: Stereo Vision and Multisensory Perception
Artificial Vision for Mobile Robots: Stereo Vision and Multisensory Perception
Direct Estimation of Structure and Motion from Multiple Frames
Direct Estimation of Structure and Motion from Multiple Frames
Hi-index | 0.00 |
The paper presents a new approach to recovering the 3D rigid shape of rigid objects from a 2D image sequence. The method has two distinguishing features:it exploits the rigidity of the object over the sequence of images, rather than over a pair of images; and, it estimates the 3D structure directly from the image intensity values, avoiding the common intermediate step of first estimating the motion induced on the image plane. The approach constructs the maximum likelihood (ML) estimate of all the shape and motion unknowns. We do not attempt the minimization of the ML energy function with respect to the entire set of unknown parameters. Rather, we start by computing the 3D motion parameters by using a robust factorization appraoch. Then, we refine the estimate of the object shape along the image sequence, by minimizing the ML-based energy function by a continuation-type method. Experimental results illustrate the performance of the method.