Part I: Manifold Learning and Clustering/Segmentation.- Practical Algorithms of Spectral Clustering: Toward Large-Scale Vision-Based Motion Analysis.- Riemannian Manifold Clustering and Dimensionality Reduction for Vision-based Analysis.- Manifold Learning for Multi-dimensional Auto-regressive Dynamical Models.- Part II: Tracking.- Mixed-state Markov Models in Image Motion Analysis.- Learning to Detect Event Sequences in Surveillance Streams at Very Low Frame Rate.- Discriminative Multiple Target Tracking.- A Framework of Wire Tracking in Image Guided Interventions.- Part III: Motion Analysis and Behavior Modeling.- An Integrated Approach to Visual Attention Modeling for Saliency Detection in Videos.- Video-based Human Motion Estimation by Part-whole Gait Manifold Learning.- Spatio-temporal Motion Pattern Models of Extremely Crowded Scenes.- Learning Behavioral Patterns of Time Series for Video-surveillance.- Part IV: Gesture and Action Recognition.- Recognition of Spatiotemporal Gestures in Sign Language using Gesture Threshold HMMs.- Learning Transferable Distance Functions for Human Action Recognition.

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