IEEE Transactions on Pattern Analysis and Machine Intelligence
The Perspective View of Three Points
IEEE Transactions on Pattern Analysis and Machine Intelligence
Estimation of Displacements from Two 3-D Frames Obtained From Stereo
IEEE Transactions on Pattern Analysis and Machine Intelligence
The Development and Comparison of Robust Methodsfor Estimating the Fundamental Matrix
International Journal of Computer Vision
Stereo Vision-Based Obstacle Detection for Partially Sighted People
ACCV '98 Proceedings of the Third Asian Conference on Computer Vision-Volume I - Volume I
Direct Estimation of Motion and Extended Scene Structure from a Moving Stereo Rig
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Visual navigation using a single camera
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
Fast camera motion estimation for hand-held devices and applications
MUM '05 Proceedings of the 4th international conference on Mobile and ubiquitous multimedia
An Introduction to Inertial and Visual Sensing
International Journal of Robotics Research
Bundle adjustment for stereoscopic 3D
MIRAGE'11 Proceedings of the 5th international conference on Computer vision/computer graphics collaboration techniques
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This paper describes a system which robustly estimates motion, and the 3D structure of a rigid environment, as a stereo vision platform moves through it. The system can cope with any camera motion, and any scene structure and is successful even in the presence of large jumps in camera position between the capture of successive image pairs, and when point matching is ambiguous. The system was developed to provide robust obstacle avoidance for a partially sighted person.The process described attempts to maximise use of the abundant information present in a stereo sequence. Key features include the use of multiple stereo match hypotheses, efficient motion computation from three images, and the use of this motion to ensure reliable matching, and to eliminate multiple stereo matches. Points are reconstructed in 3D space and tracked in a static coordinate frame with a Kalman Filter.This results in good 3D scene reconstructions. Structure which is impossible to match with certainty is absent, rather than being incorrectly reconstructed. As a result, the system is appropriate for obstacle detection. The results of processing some indoor and outdoor scenes, are given in the paper, and practical issues are highlighted throughout.