Visual Analysis of Crowded Pedestrian Scenes
نویسندگان
چکیده
The tracking of individuals in cluttered scenes has been of much interest in Machine Vision research for more than a decade. A number of algorithms have been devised to track individuals and some of the algorithms have attempted the tracking of large groups of people. In this paper we discuss how to generate automatic maps of trends of movement in complex scenes, without the use of tracking. In the proposed approach a probability density function (PDF) for the occurrence and the local orientation is generated for a scene, using a conventional foreground detection algorithm. Then, connected components and main paths are identified by exploring the two PDFs. The performance of the algorithm is then evaluated estimating errors for new instances of pedestrian patterns in the scene.
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