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A visual attention model for robot object tracking

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Abstract

Inspired by human behaviors, a robot object tracking model is proposed on the basis of visual attention mechanism, which is fit for the theory of topological perception. The model integrates the image-driven, bottom-up attention and the object-driven, top-down attention, whereas the previous attention model has mostly focused on either the bottom-up or top-down attention. By the bottom-up component, the whole scene is segmented into the ground region and the salient regions. Guided by top-down strategy which is achieved by a topological graph, the object regions are separated from the salient regions. The salient regions except the object regions are the barrier regions. In order to estimate the model, a mobile robot platform is developed, on which some experiments are implemented. The experimental results indicate that processing an image with a resolution of 752 × 480 pixels takes less than 200ms and the object regions are unabridged. The analysis obtained by comparing the proposed model with the existing model demonstrates that the proposed model has some advantages in robot object tracking in terms of speed and efficiency.

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Authors and Affiliations

  1. School of Mechanical Engineering, Dalian University of Technology, Dalian, 116024, PRC

    Jin-Kui Chu, Rong-Hua Li, Qing-Ying Li & Hong-Qing Wang

Authors
  1. Jin-Kui Chu
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  2. Rong-Hua Li
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  3. Qing-Ying Li
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  4. Hong-Qing Wang
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Corresponding author

Correspondence to Jin-Kui Chu.

Additional information

This work was supported by National Basic Research Program of China (973 Program) (No. 2006CB300407) and National Natural Science Foundation of China (No. 50775017).

Jin-Kui Chu graduated from Hangzhou Dianzi University (HDU), PRC in 1986. He received the M. Sc. degree from Xian University of Technology (XAUT), PRC in 1989, and the Ph.D. degree from Beijing University of Aeronautics and Astronautics (BUAA), PRC in 1992. He is currently a professor at School of Mechanical Engineering in Dalian University of Technology (DLUT), PRC.

His research interests include intelligent robot, biomimetic sensor, micro-actuator, and electronic measurement techniques.

Rong-Hua Li graduated from Dalian Jiaotong University (DJTU), PRC in 2005. He is currently a Ph. D. candidate at School of Mechanical Engineering in Dalian University of Technology (DLUT).

His research interests include robot vision and intelligent control.

Qing-Ying Li graduated from Zhejiang University of Technology (ZJUT), PRC in 2006. He received the M. Sc. degree from Dalian University of Technology (DLUT), PRC in 2008. He is currently working in CSR Sifang Locomotive and Rolling Stock Co. Ltd.

His research interest includes robot vision.

Hong-Qing Wang graduated from Dalian University of Technology (DLUT), PRC in 2007. He is a master student at School of Mechanical Engineering in Dalian University of Technology (DLUT).

His research interests include intelligent control of mobile robot.

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Chu, JK., Li, RH., Li, QY. et al. A visual attention model for robot object tracking. Int. J. Autom. Comput. 7, 39–46 (2010). https://doi.org/10.1007/s11633-010-0039-1

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  • DOI: https://doi.org/10.1007/s11633-010-0039-1

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