The representation, recognition, and locating of 3-d objects
International Journal of Robotics Research
Motion and Structure From Two Perspective Views: Algorithms, Error Analysis, and Error Estimation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Some Properties of the E Matrix in Two-View Motion Estimation
IEEE Transactions on Pattern Analysis and Machine Intelligence
A method of obtaining the relative positions of four points from three perspective projections
Image and Vision Computing - Special issue: BMVC 1991
Artificial Intelligence - Special volume on computer vision
Theory of Reconstruction from Image Motion
Theory of Reconstruction from Image Motion
Three D-Dynamic Scene Analysis: A Stereo Based Approach
Three D-Dynamic Scene Analysis: A Stereo Based Approach
Determining the Epipolar Geometry and its Uncertainty: A Review
International Journal of Computer Vision
Autonomous Helicopter Tracking and Localization Using a Self-surveying Camera Array
International Journal of Robotics Research
Linear Quasi-Parallax SfM Using Laterally-Placed Eyes
International Journal of Computer Vision
Self-calibration of a light striping system by matching multiple 3-D profile maps
3DIM'99 Proceedings of the 2nd international conference on 3-D digital imaging and modeling
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We describe an analytical method for recovering 3D motion and structure of four or more points from one motion of a stereo rig. The extrinsic parameters are unknown. The motion of the stereo rig is also unknown. Because of the exploitation of information redundancy, the approach gains over the traditional 驴motion and structure from motion驴 approach in that less features and less motions are required, and thus more robust estimation of motion and structure can be obtained. Since the constraint on the rotation matrix is not fully exploited in the analytical method, nonlinear minimization can be used to improve the result. We propose to estimate directly the motion and structure by minimizing the difference between the measured positions and the predicted ones in the image plane. Both computer simulated data and real data are used to validate the proposed algorithm, and very promising results are obtained.