3-D motion estimation, understanding, and prediction from nosiy image sequences
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Motion and Structure From Two Perspective Views: Algorithms, Error Analysis, and Error Estimation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Inherent Ambiguities in Recovering 3-D Motion and Structure from a Noisy Flow Field
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Data-Driven Intermediate Level Feature Extraction Algorithm
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fitting ellipses and predicting confidence envelopes using a bias corrected Kalman filter
Image and Vision Computing - Special issue: 5th Alvey vision meeting
International Journal of Computer Vision
Projectively Invariant Representations Using Implicit Algebraic Curves
ECCV '90 Proceedings of the First European Conference on Computer Vision
Analytical Results on Error Sensitivity of Motion Estimation from Two Views
ECCV '90 Proceedings of the First European Conference on Computer Vision
Image Description and 3D Interpretation From Image Trajectories Under
Image Description and 3D Interpretation From Image Trajectories Under
Inferring spatial structure from feature correspondences (machine, computer vision, robotics, mobile, artificial intelligence)
Single Axis Geometry by Fitting Conics
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part I
Circular Motion Geometry Using Minimal Data
IEEE Transactions on Pattern Analysis and Machine Intelligence
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A new technique for reconstructing the 3-D structure and motion of a scene undergoing relative rotational motion with respect to the camera is discussed. Given image correspondences of point features tracked over many frames, a two-stage technique for reconstruction is presented. A grouping algorithm that exploits spatio-temporal constraints of the common motion to achieve a reliable description of discrete point correspondences as curved trajectories in the image plane is developed. In contrast, trajectories fitted to points independent of each other lead to arbitrary image descriptions and very inaccurate 3-D parameters. A new closed-form solution, under perspective projection, for the 3-D motion and location of points from the computed image trajectories is also presented. Both stages are applied to real image sequences with good results. This approach represents a first step in a longer-term research effort examining the role of explicit spatio-temporal organization in the interpretation of scenes from dynamic images.