A Lie group formulation of robot dynamics
International Journal of Robotics Research
Fixation simplifies 3D motion estimation
Computer Vision and Image Understanding
Efficient Region Tracking With Parametric Models of Geometry and Illumination
IEEE Transactions on Pattern Analysis and Machine Intelligence
CONDENSATION—Conditional Density Propagation forVisual Tracking
International Journal of Computer Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
Application of Lie Algebras to Visual Servoing
International Journal of Computer Vision - Special issue on image-based servoing
Recursive Estimation of Motion, Structure, and Focal Length
IEEE Transactions on Pattern Analysis and Machine Intelligence
Structure from Motion Causally Integrated Over Time
IEEE Transactions on Pattern Analysis and Machine Intelligence
Hyperplane Approximation for Template Matching
IEEE Transactions on Pattern Analysis and Machine Intelligence
Making Good Features Track Better
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Lucas-Kanade 20 Years On: A Unifying Framework
International Journal of Computer Vision
Video orbits of the projective group a simple approach to featureless estimation of parameters
IEEE Transactions on Image Processing
Three-dimensional neural net for learning visuomotor coordination of a robot arm
IEEE Transactions on Neural Networks
Bidirectional composition on Lie groups for gradient-based image alignment
IEEE Transactions on Image Processing
Automatic estimation of asymmetry for gradient-based alignment of noisy images on Lie group
Pattern Recognition Letters
Advances in matrix manifolds for computer vision
Image and Vision Computing
Robust registration-based tracking by sparse representation with model update
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part III
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The main purpose of this paper is to estimate 2D and 3D transformation parameters. All the group transformations are represented in terms of their Lie algebra elements. The Lie algebra approach assures to follow the shortest path or geodesic in the involved Lie group. For the estimation of the Lie algebra parameters, we take advantage of the theory of system identification. Two experiments are presented to show the potential of the method. First, we carry out the estimation of the affine or projective parameters related to the transformation involved in monocular region tracking. Second, we develop a monocular method to estimate 3D motion of an object in the visual space. In the latter, the six parameters of the rigid motion are estimated based on measurements of the six parameters of the affine transformation in the image.