Chingchun Huang

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A major problem in metropolitan areas is searching for parking spaces. In this paper, we propose a novel method for parking space detection. Given input video captured by a camera, we can distinguish the empty spaces from the occupied spaces by using an 8-class Support Vector Machine (SVM) classifier with probabilistic outputs. Considering the inter-space(More)
In this paper, a 3-layer Bayesian hierarchical detection framework (BHDF) is proposed for robust parking space detection. In practice, the challenges of the parking space detection problem come from luminance variations, inter-occlusions among cars, and occlusions caused by environmental obstacles. Instead of determining the status of parking spaces one by(More)
In recent years, there has been an increase in video surveillance systems in public and private environments due to a heightened sense of security. The next generation of surveillance systems will be able to annotate video and locally coordinate the tracking of objects while multiplexing hundreds of video streams in real-time. In this paper, we present(More)
— A method to detect moving objects on non-stationary background is proposed. The concurrent motions of foreground and background pixels make it extremely difficult to maintain a plausible background model for background subtraction. In our method, motion fields of aligned neighboring frames are fused to reduce parallax effects in moving blob detection. A(More)
—In this paper, the main purpose is to locate, label, and correspond multiple targets with the capability of ghost suppression over a multicamera surveillance system. In practice, the challenges come from the unknown target number, the interocclusion among targets, and the ghost effect caused by geometric ambiguity. Instead of directly corresponding objects(More)
In this paper, we propose a probabilistic method to model the dynamic traffic flow across non-overlapping camera views. By assuming the transition time of object movement follows a certain global model, we may infer the time-varying traffic status in the unseen region without performing explicit object correspondence between camera views. In this paper, we(More)
In this paper, we propose an efficient way to simultaneously label and map targets over a multi-camera surveillance system. In the system, we first fuse the detection results from multiple cameras into a posterior distribution. This distribution indicates the likelihood of having some moving targets on the ground plane. Based on the distribution, isolated(More)