Motion segmentation and pose recognition with motion history gradients
Machine Vision and Applications - Special issue: IEEE WACV
Layered Representations for Human Activity Recognition
ICMI '02 Proceedings of the 4th IEEE International Conference on Multimodal Interfaces
Bayesian approach to sensor-based context awareness
Personal and Ubiquitous Computing
Proceedings of the 5th international conference on Multimodal interfaces
Layered representations for learning and inferring office activity from multiple sensory channels
Computer Vision and Image Understanding - Special issue on event detection in video
An Integrated Framework for Semantic Annotation and Adaptation
Multimedia Tools and Applications
A Model (In)Validation Approach to Gait Classification
IEEE Transactions on Pattern Analysis and Machine Intelligence
Computer Vision and Image Understanding - Special issue: Attention and performance in computer vision
Recognition of Human Motion From Qualitative Normalised Templates
Journal of Intelligent and Robotic Systems
Unusual Activity Analysis in Video Sequences
RSFDGrC '07 Proceedings of the 11th International Conference on Rough Sets, Fuzzy Sets, Data Mining and Granular Computing
Computer Vision and Image Understanding - Special issue: Attention and performance in computer vision
Recognition of human activities using SVM multi-class classifier
Pattern Recognition Letters
An exploration into activity-informed physical advertising using PEST
PERVASIVE'07 Proceedings of the 5th international conference on Pervasive computing
Comparison of human and machine recognition of everyday human actions
ICDHM'07 Proceedings of the 1st international conference on Digital human modeling
Understanding transit scenes: a survey on human behavior-recognition algorithms
IEEE Transactions on Intelligent Transportation Systems
A macro-observation scheme for abnormal event detection in daily-life video sequences
EURASIP Journal on Advances in Signal Processing - Special issue on advanced image processing for defense and security applications
A lattice-based neuro-computing methodology for real-time human action recognition
Information Sciences: an International Journal
S-SEER: selective perception in a multimodal office activity recognition system
MLMI'04 Proceedings of the First international conference on Machine Learning for Multimodal Interaction
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This paper presents a methodology for automatically identifying human action. We use a new approach to human activity recognition that incorporates a Bayesian framework. By tracking the movement of the head of the subject over consecutive frames of monocular grayscale image sequences, we recognize actions in the frontal or lateral view. Input sequences captured from a CCD camera are matched against stored models of actions. The action that is found to be closest to the input sequence is identified. In the present implementation, these actions include sitting down, standing up, bending down, getting up, hugging, squatting, rising from a squatting position, bending sideways, falling backward and walking. This methodology finds application in environments where constant monitoring of human activity is required, such as in department stores and airports.