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Fuzzy processing for active vision

机译：主动视觉的模糊处理

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Humans employ an active visual system to gather visual data from the surrounding environment. In addition to continually re-focusing the lens and adjusting the iris to control the exposure of light on to the retina, the eye constantly moves so that specific information can be focused on to the fovea - the part of the retina capable of defining fine detail. The target location when the eye moves is determined by the attention of the viewer. The attention of the viewer is drawn towards regions within the environment that are interesting or salient, i.e. they contain visual or semantic information. A mobile robot traversing within its environment has to identify and locate landmarks and other mobile entities as part of its navigational processes. The ability to efficiently analyze visual data captured from the environment and relate this to information from its internal map is very important. In this work a technique is described that uses semantic data to direct attention towards regions of interest within a simple environment and systematically search other areas of the environment. A fuzzy system lies at the heart of the technique that reasons with historical and environmental data in order to influence the search patterns. A Kohonen self-organizing map is used for object classification. Experimental data will be provided to illustrate the success and efficiency of the technique and conclusions will be drawn that discuss future work.
机译：人类采用主动的视觉系统从周围环境中收集视觉数据。除了不断地重新聚焦晶状体并调节虹膜以控制光在视网膜上的曝光外，眼睛还会不断移动，以便可以将特定信息聚焦在中央凹上-视网膜的一部分可以定义精细的细节。眼睛移动时的目标位置由观看者的注意力确定。观看者的注意力吸引到环境中有趣或显着的区域，即它们包含视觉或语义信息。作为其导航过程的一部分，在其环境中穿越的移动机器人必须识别并定位地标和其他移动实体。有效分析从环境中捕获的视觉数据并将其与内部地图中的信息相关联的能力非常重要。在这项工作中，描述了一种技术，该技术使用语义数据将注意力引向简单环境中的关注区域，并系统地搜索环境的其他区域。模糊系统是该技术的核心，它会根据历史和环境数据进行推理，以影响搜索模式。 Kohonen自组织图用于对象分类。将提供实验数据来说明该技术的成功和效率，并将得出讨论未来工作的结论。

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