Robust regression and outlier detection
Robust regression and outlier detection
Performance of optical flow techniques
International Journal of Computer Vision
Design and Use of Linear Models for Image Motion Analysis
International Journal of Computer Vision
Multiple view geometry in computer vision
Multiple view geometry in computer vision
Motion and Structure from Image Sequences
Motion and Structure from Image Sequences
Self-Calibration from Image Derivatives
International Journal of Computer Vision
Linear Multi View Reconstruction and Camera Recovery Using a Reference Plane
International Journal of Computer Vision
Estimating 3D camera motion without correspondences using a search for the best structure
Pattern Recognition Letters
Motion Estimation Using the Differential Epipolar Equation
ICPR '00 Proceedings of the International Conference on Pattern Recognition - Volume 3
A New Approach to Hand-Eye Calibration
ICPR '00 Proceedings of the International Conference on Pattern Recognition - Volume 1
Vision-Based Camera Motion Recovery for Augmented Reality
CGI '04 Proceedings of the Computer Graphics International
Beyond RANSAC: User Independent Robust Regression
CVPRW '06 Proceedings of the 2006 Conference on Computer Vision and Pattern Recognition Workshop
Genetic Algorithm SAmple Consensus (GASAC) - A Parallel Strategy for Robust Parameter Estimation
CVPRW '06 Proceedings of the 2006 Conference on Computer Vision and Pattern Recognition Workshop
Design Through Operation of an Image-Based Velocity Estimation System for Mars Landing
International Journal of Computer Vision
Stereo geometry from 3D ego-motion streams
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Apparent 3-D camera velocity-extraction and applications
IEEE Transactions on Circuits and Systems for Video Technology
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This paper presents a new technique to the instantaneous 3D motion estimation. The main contributions are as follows. First, we show that the 3D camera or scene velocity can be retrieved from image derivatives only assuming that the scene contains a dominant plane. Second, we propose a new robust algorithm that simultaneously provides the Least Trimmed Square solution and the percentage of inliers-the non-contaminated data. Experiments on both synthetic and real image sequences demonstrated the effectiveness of the developed method. Those experiments show that the new robust approach can outperform classical robust schemes.