Motion Capture and Pose Estimation.- Marker-Less 3D Feature Tracking for Mesh-Based Human Motion Capture.- Boosted Multiple Deformable Trees for Parsing Human Poses.- Gradient-Enhanced Particle Filter for Vision-Based Motion Capture.- Multi-activity Tracking in LLE Body Pose Space.- Exploiting Spatio-temporal Constraints for Robust 2D Pose Tracking.- Efficient Upper Body Pose Estimation from a Single Image or a Sequence.- Real-Time and Markerless 3D Human Motion Capture Using Multiple Views.- Modeling Human Locomotion with Topologically Constrained Latent Variable Models.- Silhouette Based Generic Model Adaptation for Marker-Less Motion Capturing.- Body and Limb Tracking and Segmentation.- 3D Hand Tracking in a Stochastic Approximation Setting.- Nonparametric Density Estimation with Adaptive, Anisotropic Kernels for Human Motion Tracking.- Multi Person Tracking Within Crowded Scenes.- Joint Appearance and Deformable Shape for Nonparametric Segmentation.- Robust Spectral 3D-Bodypart Segmentation Along Time.- Articulated Object Registration Using Simulated Physical Force/Moment for 3D Human Motion Tracking.- An Ease-of-Use Stereo-Based Particle Filter for Tracking Under Occlusion.- Activity Recognition.- Semi-Latent Dirichlet Allocation: A Hierarchical Model for Human Action Recognition.- Recognizing Activities with Multiple Cues.- Human Action Recognition Using Distribution of Oriented Rectangular Patches.- Human Motion Recognition Using Isomap and Dynamic Time Warping.- Behavior Histograms for Action Recognition and Human Detection.- Learning Actions Using Robust String Kernels.