Human motion analysis: a review
Computer Vision and Image Understanding
A Bayesian Computer Vision System for Modeling Human Interactions
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multiobject Behavior Recognition by Event Driven Selective Attention Method
IEEE Transactions on Pattern Analysis and Machine Intelligence
Computer Graphics
Extracting Semantic Information from Basketball Video Based on Audio-Visual Features
CIVR '02 Proceedings of the International Conference on Image and Video Retrieval
Content Based Analysis for Video from Snooker Broadcasts
CIVR '02 Proceedings of the International Conference on Image and Video Retrieval
Singularity Analysis for Articulated Object Tracking
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Gesture Modeling and Recognition Using Finite State Machines
FG '00 Proceedings of the Fourth IEEE International Conference on Automatic Face and Gesture Recognition 2000
Segmentation and Tracking of Interacting Human Body Parts under Occlusion and Shadowing
MOTION '02 Proceedings of the Workshop on Motion and Video Computing
Model-Based Human Body Tracking
ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 1 - Volume 1
Recognition of Human Interaction Using Multiple Features in Grayscale Images
ICPR '00 Proceedings of the International Conference on Pattern Recognition - Volume 1
Integrated Image and Speech Analysis for Content-Based Video Indexing
ICMCS '96 Proceedings of the 1996 International Conference on Multimedia Computing and Systems
Recognition of two-person interactions using a hierarchical Bayesian network
IWVS '03 First ACM SIGMM international workshop on Video surveillance
Boosted string representation and its application to video surveillance
Pattern Recognition
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
The state of the art in image and video retrieval
CIVR'03 Proceedings of the 2nd international conference on Image and video retrieval
Tracking and classifying of human motions with Gaussian process annealed particle filter
ACCV'07 Proceedings of the 8th Asian conference on Computer vision - Volume Part I
Using Gaussian processes for human tracking and action classification
ISVC'07 Proceedings of the 3rd international conference on Advances in visual computing - Volume Part I
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Recognition of human interactions in a video is useful for video annotation, automated surveillance, and content-based video retrieval. This paper presents a model-based approach to motion tracking and recognition of human interactions using multi-layer finite state automata (FA). The system is used for widely-available, static-background monocular surveillance videos. A three-dimensional human body model is built using a sphere and cylinders and is projected on a two-dimensional image plane to fit the foreground image silhouette. We convert the human motion tracking problem into a parameter optimization problem without the need to compute inverse kinematics. A cost functional is used to estimate the degree of the overlap between the foreground input image silhouette and a projected three-dimensional body model silhouette. Motion data obtained from the tracker is analyzed in terms of feet, torso, and hands by a behavior recognition system. The recognition model represents human behavior as a sequence of states that register the configuration of individual body parts in space and time. In order to overcome the exponential growth of the number of states that usually occurs in single-level FA, we propose a multi-layer FA that abstracts states and events from motion data at multiple levels: low-level FA analyzes body parts only, and high-level FA analyzes the human interaction. Motion tracking results from video sequences are presented. Our recognition framework successfully recognizes various human interactions such as approaching, departing, pushing, pointing, and handshaking.