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We address the problem of classifying human actions using a single depth sensor camera. In this work, we propose an angular representation to model the relationship between the joints in human skeleton. This representation helps cope with noisy data while enhances both computational efficiency and flexibility. Also, we propose to use Hidden Markov Model(More)
We present a video monitoring system to count the number of people in an open area such as an airport, a bus station, or a shopping mall using a single camera. Our system automatically infers the number of people based on a novel multi-people tracker. The tracking framework is formulated as a data association problem, in which the people are detected in(More)
A piloted comparison of rigid and aeroelastic blade-element rotor models was conducted on the Crew Station Research and Development Facility (CSRDF) at Ames Research Center. FLIGHTLAB, a new simulation development and analysis tool, was used to implement these models in real time using parallel processing technology. Pilot comments and quantitative analysis(More)
We present a framework addressing the problem of multi-pedestrian tracking in a crowded scene from a single view camera. The key factor to improve the performance of tracking results in data association is providing an effective appearance model for each target. There are many efforts in developing such models in generative and discriminative ways to either(More)
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