【主 講 人】林道通 教授兼教務長 國立台北大學資訊工程學系
【時 間】103年10月24日(五) 14：00 ~ 16：00
【地 點】工四講堂
【題 目】Crossroad Traffic Surveillance Using Superpixel Tracking and Vehicle Trajectory Analysis
Abstract::As the density of road traffic increases, it becomes ever more important to analyze the traffic information for improving the transportation safety and reducing vehicle congestion. Vehicle trajectory may provide useful information. This paper presents a novel vehicle trajectory analysis system based on computer vision technology. By utilizing superpixel segmentation and object modeling, the proposed approach is able to increase the robustness of object matching and tracking overtime. As the density of road traffic increases, it becomes ever more important to analyze the traffic information for improving the transportation safety and reducing vehicle congestion. We have developed an algorithm which is capable of detecting illegal-left-turn vehicle from a forward-only-lane using the proposed trajectory map constructed based on the vehicles trajectory. Experimental results show that correct object tracking rate is as high as 98.8%. The proposed system can handle illegal-left-turn vehicle detection on the crossroad with superior performance.
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(1)Join the seminar session in English (or with slides in English) and finish your report in class.
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