3D Tracking and Classification System Using a Monocular Camera

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• 作者：George Bardas ; Stefanos Astaras ; Sotirios DiamantasR30
• 关键词：Visual tracking ; 3D tracking ; Visual measurements ; Particle filters ; Likelihood function ; Fusion
• 刊名：Wireless Personal Communications
• 出版年：2017
• 出版时间：January 2017
• 年：2017
• 卷：92
• 期：1
• 页码：63-85
• 全文大小：
• 刊物类别：Engineering
• 刊物主题：Communications Engineering, Networks; Signal,Image and Speech Processing; Computer Communication Networks;
• 出版者：Springer US
• ISSN：1572-834X
• 卷排序：92

文摘

This paper details a 3D tracking and recognition system using a single camera. The system is able to track and classify targets in outdoors and indoors scenarios, as long as they move (at least approximately) on a plane. The system first detects and validates targets and then tracks them in a state-space employing cylindrical models (horizontal and vertical position on the ground, their radius and height) utilising Particle Filters. The tracker fuses visual measurements that utilise the targets’ foreground and colour models. Finally the system classifies the tracked objects based on the visual metrics extracted by our algorithm. We have tested our model in an outdoor setting using humans and automobiles passing through the field of view of the camera at various speeds and distances. The results presented in this paper show the validity our approach.