Lucas-Kanade 20 Years On: A Unifying Framework
International Journal of Computer Vision
Media sharing based on colocation prediction in urban transport
Proceedings of the 14th ACM international conference on Mobile computing and networking
Sensing and predicting the pulse of the city through shared bicycling
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
Coverage management for mobile targets in visual sensor networks
Proceedings of the 15th ACM international conference on Modeling, analysis and simulation of wireless and mobile systems
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Outdoor surveillance cameras have become prevalent as part of the urban infrastructure, and provided a good data source for studying urban dynamics. In this work, we provide a spatial-temporal analysis of 8 weeks of video data collected from the large outdoor camera network at UCSB campus, which consists of 27 cameras. We first apply simple vision algorithm to extract the crowdedness information in the scene. Then we further explore the relationship between the traffic pattern observed from the cameras with activities in the nearby area using additional knowledge such as campus class schedule. Finally we investigate the potential of discovering aggregated human movement pattern by assuming a simple probabilistic model. Experiment has shown promising results using the proposed method.