Research on bank intelligent video image processing and monitoring control system based on OpenCV
ASID'09 Proceedings of the 3rd international conference on Anti-Counterfeiting, security, and identification in communication
Survey on classifying human actions through visual sensors
Artificial Intelligence Review
Physical activity recognition using multiple sensors embedded in a wearable device
ACM Transactions on Embedded Computing Systems (TECS) - Special issue on embedded systems for interactive multimedia services (ES-IMS)
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We propose an algorithm for articulated human motion segmentation that estimates parametric motions of body parts and segments images into moving regions accordingly. Our approach combines robust optical flow estimation, RANSAC, and region segmentation using color and Gaussian shape priors. This combination results in an algorithm that can robustly estimate and segment multiple motions, even for moving regions with small support and in low-resolution images. Based on the raw motion segmentation, consistent body motions are detected over time to characterize human activity. The effectiveness of this approach is demonstrated in a real scenario: characterizing dining activities of patients at a nursing home.