System identification: theory for the user
System identification: theory for the user
Stochastic model for boundary detection
Image and Vision Computing - Special issue: papers from the second Alvey Vision Conference
Artificial intelligence (2nd ed.)
Artificial intelligence (2nd ed.)
Tracking and data association
Hands: a pattern theoretic study of biological shapes
Hands: a pattern theoretic study of biological shapes
The DigitalDesk calculator: tangible manipulation on a desk top display
UIST '91 Proceedings of the 4th annual ACM symposium on User interface software and technology
Fundamentals of speech recognition
Fundamentals of speech recognition
Learning to track the visual motion of contours
Artificial Intelligence - Special volume on computer vision
CONDENSATION—Conditional Density Propagation forVisual Tracking
International Journal of Computer Vision
Proceedings of the 1998 conference on Advances in neural information processing systems II
Learning nonlinear dynamical systems using an EM algorithm
Proceedings of the 1998 conference on Advances in neural information processing systems II
Hidden Markov Models for Speech Recognition
Hidden Markov Models for Speech Recognition
Computer Controlled Systems: Theory and Design
Computer Controlled Systems: Theory and Design
Contour Tracking by Stochastic Propagation of Conditional Density
ECCV '96 Proceedings of the 4th European Conference on Computer Vision-Volume I - Volume I
Learning Dynamics of Complex Motions from Image Sequences
ECCV '96 Proceedings of the 4th European Conference on Computer Vision-Volume I - Volume I
ICONDENSATION: Unifying Low-Level and High-Level Tracking in a Stochastic Framework
ECCV '98 Proceedings of the 5th European Conference on Computer Vision-Volume I - Volume I
A Smoothing Filter for CONDENSATION
ECCV '98 Proceedings of the 5th European Conference on Computer Vision-Volume I - Volume I
Learning and Recognizing Human Dynamics in Video Sequences
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
A state-based technique for the summarization and recognition of gesture
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
Learning Dynamical Models Using Expectation-Maximisation
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
A Probabilistic Contour Discriminant for Object Localisation
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
A Mixed-State Condensation Tracker with Automatic Model-Switching
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Motion texture: a two-level statistical model for character motion synthesis
Proceedings of the 29th annual conference on Computer graphics and interactive techniques
Online Fingerprint Template Improvement
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multimodal Shape Tracking with Point Distribution Models
Proceedings of the 24th DAGM Symposium on Pattern Recognition
Probabilistic recognition of human faces from video
Computer Vision and Image Understanding - Special issue on Face recognition
Learning-based tracking of complex non-rigid motion
Journal of Computer Science and Technology
UAI '04 Proceedings of the 20th conference on Uncertainty in artificial intelligence
A Model (In)Validation Approach to Gait Classification
IEEE Transactions on Pattern Analysis and Machine Intelligence
Visual tracking and recognition using probabilistic appearance manifolds
Computer Vision and Image Understanding
Temporal motion models for monocular and multiview 3D human body tracking
Computer Vision and Image Understanding - Special issue on modeling people: Vision-based understanding of a person's shape, appearance, movement, and behaviour
Classifying functional time series
Signal Processing
Inferring facial expressions from videos: Tool and application
Image Communication
Simultaneous Facial Action Tracking and Expression Recognition in the Presence of Head Motion
International Journal of Computer Vision
Learning and Inferring Motion Patterns using Parametric Segmental Switching Linear Dynamic Systems
International Journal of Computer Vision
Automated detection of unusual events on stairs
Image and Vision Computing
Detecting motion patterns via direction maps with application to surveillance
Computer Vision and Image Understanding
Unsupervised view and rate invariant clustering of video sequences
Computer Vision and Image Understanding
Joint trajectory tracking and recognition based on bi-directional nonlinear learning
Image and Vision Computing
Hybrid Dynamical Models of Human Motion for the Recognition of Human Gaits
International Journal of Computer Vision
Data-driven MCMC for learning and inference in switching linear dynamic systems
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 2
Visual tracking and recognition using probabilistic appearance manifolds
Computer Vision and Image Understanding
Efficient particle filtering using RANSAC with application to 3D face tracking
Image and Vision Computing
Variable duration motion texture for human motion modeling
PRICAI'06 Proceedings of the 9th Pacific Rim international conference on Artificial intelligence
ACIVS'07 Proceedings of the 9th international conference on Advanced concepts for intelligent vision systems
Adaptive appearance model and condensation algorithm for robust face tracking
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans - Special issue on recent advances in biometrics
Tracking and activity recognition through consensus in distributed camera networks
IEEE Transactions on Image Processing - Special section on distributed camera networks: sensing, processing, communication, and implementation
3D model based expression tracking in intrinsic expression space
FGR' 04 Proceedings of the Sixth IEEE international conference on Automatic face and gesture recognition
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
Video-based face recognition using probabilistic appearance manifolds
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
A grid-based Bayesian approach to robust visual tracking
Digital Signal Processing
Hierarchical clustering of dynamical systems based on eigenvalue constraints
ICAPR'05 Proceedings of the Third international conference on Advances in Pattern Recognition - Volume Part I
MICCAI'06 Proceedings of the 9th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part I
ACIVS'06 Proceedings of the 8th international conference on Advanced Concepts For Intelligent Vision Systems
Predictive camera tracking for bronchoscope simulation with CONDensation
MICCAI'05 Proceedings of the 8th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part I
Spatio-temporal target-measure association using an adaptive geometrical approach
Pattern Recognition Letters
Multi-mode saliency dynamics model for analyzing gaze and attention
Proceedings of the Symposium on Eye Tracking Research and Applications
Integrated tracking and recognition of human activities in shape space
ICVGIP'06 Proceedings of the 5th Indian conference on Computer Vision, Graphics and Image Processing
Estimating the non-linear dynamics of free-flying objects
Robotics and Autonomous Systems
Modeling video viewing behaviors for viewer state estimation
Proceedings of the 20th ACM international conference on Multimedia
Dynamic context for tracking behind occlusions
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part V
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Standard, exact techniques based on likelihood maximization are available for learning Auto-Regressive Process models of dynamical processes. The uncertainty of observations obtained from real sensors means that dynamics can be observed only approximately. Learning can still be achieved via 驴EM-K驴驴Expectation-Maximization (EM) based on Kalman Filtering. This cannot handle more complex dynamics, however, involving multiple classes of motion. A problem arises also in the case of dynamical processes observed visually: background clutter arising for example, in camouflage, produces non-Gaussian observation noise. Even with a single dynamical class, non-Gaussian observations put the learning problem beyond the scope of EM-K. For those cases, we show here how 驴EM-C驴驴based on the Condensation algorithm which propagates random 驴particle-sets,驴 can solve the learning problem. Here, learning in clutter is studied experimentally using visual observations of a hand moving over a desktop. The resulting learned dynamical model is shown to have considerable predictive value: When used as a prior for estimation of motion, the burden of computation in visual observation is significantly reduced. Multiclass dynamics are studied via visually observed juggling; plausible dynamical models have been found to emerge from the learning process, and accurate classification of motion has resulted. In practice, EM-C learning is computationally burdensome and the paper concludes with some discussion of computational complexity.