MLMotion08
* *Machine Learning for Vision-based Motion Analysis
* Approximate RBF kernel SVM and its applications in pedestrian classification
* Capturing Video Structure with Mixture of Probabilistic Index Maps
* Combination of supervised and unsupervised methods for navigation path mining
* Facial motion analysis using clustered shortest path tree registration
* Flexible dictionaries for action classification
* framework for indexing human actions in video, A
* From learning individual actions to 3D animation of team sports
* From local temporal correlation to global anomaly detection
* Human motion tracking using a color-based particle filter driven by optical flow
* Independent viewpoint silhouette-based human action modeling and recognition
* Learning Bayesian tracking for motion estimation
* Learning Pullback metrics for linear models
* Linear and Non-Linear Models for Monocular 3D Motion Capture
* new spatio-temporal MRF framework for video-based object segmentation, A
* Optimizing trajectories clustering for activity recognition
* Self-similar regularization of optic-flow for turbulent motion estimation
* Simultaneous learning of motion and appearance
* Spatio-temporal feature recognition using randomised Ferns
* Spatio-temporal motion pattern modeling of extremely crowded scenes
* Super-resolved digests of humans in video
* Unsupervised learning of behavioural patterns for video-surveillance
22 for MLMotion08