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A Visual Attention Model for Robot Object Tracking 被引量:3
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作者 Jin-Kui Chu Rong-Hua Li Qing-Ying Li Hong-Qing Wang School of Mechanical Engineering, Dalian University of Technology, Dalian 116024, PRC 《International Journal of Automation and computing》 EI 2010年第1期39-46,共8页
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-u... 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 200 ms 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. 展开更多
关键词 Object tracking visual attention topological perception salient regions weighted similarity equation
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