International Journal of Computer Vision
Geometric optimization methods for adaptive filtering
Geometric optimization methods for adaptive filtering
3-D interpretation of optical flow by renormalization
International Journal of Computer Vision
Linear subspace methods for recovering translational direction
Proceedings of the 1991 York conference on Spacial vision in humans and robots
On the Optimization Criteria Used in Two-View Motion Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
The Geometry of Algorithms with Orthogonality Constraints
SIAM Journal on Matrix Analysis and Applications
Optimal Structure from Motion: Local Ambiguities and Global Estimates
International Journal of Computer Vision
A Mathematical Introduction to Robotic Manipulation
A Mathematical Introduction to Robotic Manipulation
Theory of Reconstruction from Image Motion
Theory of Reconstruction from Image Motion
3D Object recognition in cluttered environments by segment-based stereo vision
International Journal of Computer Vision
Optimal Motion and Structure Estimation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Structure and Motion from Line Segments in Multiple Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
A unifying framework for structure and motion recovery from image sequences
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
A differential geometric approach to computer vision and its applications in control
A differential geometric approach to computer vision and its applications in control
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3D reconstruction from image correspondences has been studied in the two respects: one is the unifying framework, often called structure from motion, where motion and structure are estimated simultaneously, and the other is the decoupling framework, often called motion estimation, where motion is estimated separately from structure. The two approaches have both some advantages and disadvantages at the same time. So, in this paper, we first show the relations between structure from motion using bundle-adjustment, a representative approach in the unifying framework, and motion estimation using epipolar geometry, that in the decoupling framework. Based on the results we also present a computationally efficient algorithm solving the bundle-adjustment-based structure from motion problem, where motion and structure are estimated separately. Our research has some significance in the two respects. First, although some researchers have found the relations between the optimization criteria used in epipolar-geometry-based approaches, the results have rarely extended to those in other approaches, e.g. bundle-adjustment approach. Second, our proposed algorithm can take the advantages of the unifying and the decoupling frameworks, e.g., benefit of a low-dimensional search space and prevention of performance degradation in the decoupling framework.