Neural networks and fuzzy systems: a dynamical systems approach to machine intelligence
Neural networks and fuzzy systems: a dynamical systems approach to machine intelligence
W4: Real-Time Surveillance of People and Their Activities
IEEE Transactions on Pattern Analysis and Machine Intelligence
Tracking and Object Classification for Automated Surveillance
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part IV
Real-time Human Motion Analysis by Image Skeletonization
WACV '98 Proceedings of the 4th IEEE Workshop on Applications of Computer Vision (WACV'98)
Recognition of Human Motion From Qualitative Normalised Templates
Journal of Intelligent and Robotic Systems
Classifying and tracking multiple persons for proactive surveillance of mass transport systems
AVSS '07 Proceedings of the 2007 IEEE Conference on Advanced Video and Signal Based Surveillance
Classification of gait types based on the duty-factor
AVSS '07 Proceedings of the 2007 IEEE Conference on Advanced Video and Signal Based Surveillance
Moments and wavelets for classification of human gestures represented by spatio-temporal templates
AI'04 Proceedings of the 17th Australian joint conference on Advances in Artificial Intelligence
A survey on visual surveillance of object motion and behaviors
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Probabilistic posture classification for Human-behavior analysis
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Human Body Posture Classification by a Neural Fuzzy Network and Home Care System Application
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Automatic gait recognition based on statistical shape analysis
IEEE Transactions on Image Processing
Efficient moving object segmentation algorithm using background registration technique
IEEE Transactions on Circuits and Systems for Video Technology
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Motion classification is the first step of gait recognition. The classification of motion is conducted, and behavior validity can be made under specific scenarios. In order to identify people movement in an Intelligent Security Monitoring System, moving body is detected and the boundary is extracted. The paper proposes a complex number notation based on centroid in order to indicate a pedestrian's movements. And according to the different sorts of movements, a set of standard image contours are made. A Procrustes shape analysis method is presented in order to get the degree to which two contours are resembled. Finally lying, bending, sitting, walking, side walking, jumping, crouching, uphill and downhill is given with a 72.2% recognition rate achieved.