Introduction to data compression
Introduction to data compression
The visual analysis of human movement: a survey
Computer Vision and Image Understanding
Human motion analysis: a review
Computer Vision and Image Understanding
W4: Real-Time Surveillance of People and Their Activities
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Bayesian Computer Vision System for Modeling Human Interactions
IEEE Transactions on Pattern Analysis and Machine Intelligence
A survey of computer vision-based human motion capture
Computer Vision and Image Understanding - Modeling people toward vision-based underatanding of a person's shape, appearance, and movement
M2Tracker: A Multi-View Approach to Segmenting and Tracking People in a Cluttered Scene
International Journal of Computer Vision
FG '00 Proceedings of the Fourth IEEE International Conference on Automatic Face and Gesture Recognition 2000
Layered Representations for Human Activity Recognition
ICMI '02 Proceedings of the 4th IEEE International Conference on Multimodal Interfaces
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
An Invitation to 3-D Vision: From Images to Geometric Models
An Invitation to 3-D Vision: From Images to Geometric Models
Tracking Multiple Humans in Complex Situations
IEEE Transactions on Pattern Analysis and Machine Intelligence
Semantic-level Understanding of Human Actions and Interactions using Event Hierarchy
CVPRW '04 Proceedings of the 2004 Conference on Computer Vision and Pattern Recognition Workshop (CVPRW'04) Volume 1 - Volume 01
Distributed Interactive Video Arrays for Event Capture and Enhanced Situational Awareness
IEEE Intelligent Systems
3D Shape Context Based Gesture Analysis Integrated with Tracking using Omni Video Array
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops - Volume 03
Principal Axis-Based Correspondence between Multiple Cameras for People Tracking
IEEE Transactions on Pattern Analysis and Machine Intelligence
Simultaneous tracking of multiple body parts of interacting persons
Computer Vision and Image Understanding
Analysis and query of person-vehicle interactions in homography domain
Proceedings of the 4th ACM international workshop on Video surveillance and sensor networks
Machine Vision and Applications
Real-time foreground-background segmentation using codebook model
Real-Time Imaging
An analytic distance metric for Gaussian mixture models with application in image retrieval
ICANN'05 Proceedings of the 15th international conference on Artificial neural networks: formal models and their applications - Volume Part II
A multiview approach to tracking people in crowded scenes using a planar homography constraint
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part IV
Multi-perspective video analysis of persons and vehicles for enhanced situational awareness
ISI'06 Proceedings of the 4th IEEE international conference on Intelligence and Security Informatics
Dynamic context capture and distributed video arrays for intelligent spaces
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
PRISMATICA: toward ambient intelligence in public transport environments
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Consistent labeling of tracked objects in multiple cameras with overlapping fields of view
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multi-view Video Analysis of Humans and Vehicles in an Unconstrained Environment
ISVC '08 Proceedings of the 4th International Symposium on Advances in Visual Computing
A survey on vision-based human action recognition
Image and Vision Computing
Social interaction detection using a multi-sensor approach
Proceedings of the 21st ACM international conference on Multimedia
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This paper presents a new two-stage multi-view framework for the analysis of human interactions and activities. The analysis is performed in a distributed multi-view vision system that synergistically integrates track- and body-level processing. The proposed framework is geared toward versatile and easily-deployable systems that do not require careful camera calibration. The main contributions of the paper are as follows; (1) context-dependent view switching for occlusion handling, (2) a method for switching the two-stage analysis between the track- and body-level processing, and (3) a hypothesis-verification paradigm for top-down feedback that exploits the spatio-temporal constraints inherent in human interaction. An experimental evaluation shows the efficacy of the proposed system for analyzing multi-person interactions.