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论文类型： 期刊论文

发表时间： 2017-01-01

发表刊物： International Journal of Embedded Systems

收录刊物： Scopus、EI

卷号： 9

期号： 1

页面范围： 54-60

ISSN号： 17411068

摘要： In this paper, we address the problem of automatically detecting and tracking a variable number of objects in complex scenes using a RGB-D sensor on the robot system. We propose a novel approach for multi-object detecting by fusing RGB information and depth information. Meanwhile, this paper presents a robust multi-cue approach for multi-object tracking. A spatiotemporal object representation is proposed, which combines a generative colour model and a discriminative texture classifier. We employ a Bayesian framework based on particle filtering to achieve integrated object detection and tracking from a robot vision system. The experimental results show that the proposed method yields good tracking performance in real world environment.