This paper describes a visual perception system for a social robot. The central part of this system is an artificial attention mechanism that discriminates the most relevant information from all the visual information perceived by the robot. It is composed by three stages. At the preattentive stage, the concept of saliency is implemented based on ‘proto-objects’ [37]. From these objects, different saliency maps are generated. Then, the semiattentive stage identifies and tracks significant items according to the tasks to accomplish. This tracking process allows to implement the ‘inhibition of return’. Finally, the attentive stage fixes the field of attention to the most relevant object depending on the behaviours to carry out. Three behaviours have been implemented and tested which allow the robot to detect visual landmarks in an initially unknown environment, and to recognize and capture the upper-body motion of people interested in interact with it.

中文翻译：

---

社交机器人的视觉注意机制

本文介绍了社交机器人的视觉感知系统。该系统的中心部分是人为注意机制，可从机器人感知到的所有视觉信息中区分出最相关的信息。它由三个阶段组成。在注意阶段，显着性的概念是基于“原型对象” [37]来实现的。从这些对象生成不同的显着性图。然后，半专注阶段根据要完成的任务识别并跟踪重要项目。这种跟踪过程可以实现“抑制回报”。最后，注意阶段会根据要执行的行为将注意力集中在最相关的对象上。