Learned Models for Estimation of Rigid and ArticulatedHuman Motion from Stationary or Moving Camera
International Journal of Computer Vision
Design and Use of Linear Models for Image Motion Analysis
International Journal of Computer Vision
Image Registration Using Wavelet-Based Motion Model
International Journal of Computer Vision
Correspondence with Cumulative Similiarity Transforms
IEEE Transactions on Pattern Analysis and Machine Intelligence
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part I
Automatic Detection and Tracking of Human Motion with a View-Based Representation
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part I
Tracking and Rendering Using Dynamic Textures on Geometric Structure from Motion
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part II
Qualitative Spatiotemporal Analysis Using an Oriented Energy Representation
ECCV '00 Proceedings of the 6th European Conference on Computer Vision-Part II
A Framework for Robust Subspace Learning
International Journal of Computer Vision - Special Issue on Computational Vision at Brown University
Subtly Different Facial Expression Recognition and Expression Intensity Estimation
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
A Radial Cumulative Similarity Transform for Robust Image Correspondence
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Motion Feature Detection Using Steerable Flow Fields
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Tracking People with Twists and Exponential Maps
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Recognizing image "style" and activities in video using local features and naive Bayes
Pattern Recognition Letters
Twist Based Acquisition and Tracking of Animal and Human Kinematics
International Journal of Computer Vision
Efficient Hodge-Helmholtz decomposition of motion fields
Pattern Recognition Letters - Special issue: Advances in pattern recognition
International Journal of Computer Vision
Combining Generative and Discriminative Models in a Framework for Articulated Pose Estimation
International Journal of Computer Vision
Computational studies of human motion: part 1, tracking and motion synthesis
Foundations and Trends® in Computer Graphics and Vision
A recursive approach to the design of adjustable linear models for complex motion analysis
SPPR'07 Proceedings of the Fourth conference on IASTED International Conference: Signal Processing, Pattern Recognition, and Applications
A fast data collection and augmentation procedure for object recognition
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 3
A recursive approach to the design of adjustable linear models for complex motion analysis
SPPRA '07 Proceedings of the Fourth IASTED International Conference on Signal Processing, Pattern Recognition, and Applications
An adaptive confidence measure for optical flows based on linear subspace projections
Proceedings of the 29th DAGM conference on Pattern recognition
PCA-based magnetic field modeling: application for on-line MR temperature monitoring
MICCAI'07 Proceedings of the 10th international conference on Medical image computing and computer-assisted intervention
Dynamic color flow: a motion-adaptive color model for object segmentation in video
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part V
Complex motion models for simple optical flow estimation
Proceedings of the 32nd DAGM conference on Pattern recognition
On performance analysis of optical flow algorithms
Proceedings of the 15th international conference on Theoretical Foundations of Computer Vision: outdoor and large-scale real-world scene analysis
Common-sense reasoning for human action recognition
Pattern Recognition Letters
Machine Vision and Applications
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A framework for learning parameterized models of optical flow from image sequences is presented. A class of motions is represented by a set of orthogonal basis flow fields that are computed from a training set using principal component analysis. Many complex image motions can be represented by a linear combination of a small number of these basis flows. The learned motion models may be used for optical flow estimation and for model-based recognition. For optical flow estimation we describe a robust, multi-resolution scheme for directly computing the parameters of the learned flow models from image derivatives. As examples we consider learning motion discontinuities, non-rigid motion of human mouths, and articulated human motion.