Items related to Machine Learning for Vision-Based Motion Analysis
Synopsis
Part I: Manifold Learning and Clustering/Segmentation
Practical Algorithms of Spectral Clustering: Toward Large-Scale Vision-Based Motion Analysis
Tomoya Sakai, and Atsushi Imiya
Riemannian Manifold Clustering and Dimensionality Reduction for Vision-based Analysis
Alvina Goh
Manifold Learning for Multi-dimensional Auto-regressive Dynamical Models
Fabio Cuzzolin
Part II: Tracking
Mixed-state Markov Models in Image Motion Analysis
Tomás Crivelli, Patrick Bouthemy, Bruno Cernuschi Frías, and Jian-feng Yao
Learning to Detect Event Sequences in Surveillance Streams at Very Low Frame Rate
Paolo Lombardi, and Cristina Versino
Discriminative Multiple Target Tracking
Xiaoyu Wang, Gang Hua, and Tony X. Han
A Framework of Wire Tracking in Image Guided Interventions
Peng Wang, Andreas Meyer, Terrence Chen, Shaohua K. Zhou, and Dorin Comaniciu
Part III: Motion Analysis and Behavior Modeling
An Integrated Approach to Visual Attention Modeling for Saliency Detection in Videos
Sunaad Nataraju, Vineeth Balasubramanian, and Sethuraman Panchanathan
Video-based Human Motion Estimation by Part-whole Gait Manifold Learning
Guoliang Fan, and Xin Zhang
Spatio-temporal Motion Pattern Models of Extremely Crowded Scenes
Louis Kratz and Ko Nishino
Learning Behavioral Patterns of Time Series for Video-surveillance
Nicoletta Noceti, Matteo Santoro, and Francesca Odone
Part IV: Gesture and Action Recognition
Recognition of Spatiotemporal Gestures in Sign Language using Gesture Threshold HMMs
Daniel Kelly, John Mc Donald and Charles Markham
Learning Transferable Distance Functions for Human Action Recognition
Weilong Yang, YangWang, and Greg Mori
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