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The emergence of attention by population-based inference and its role in distributed processing and cognitive control of vision

机译:基于人群的推理引起注意的出现及其在视觉的分布式处理和认知控制中的作用

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Technologies such as video surveillance and vision guided robotics require flexible vision systems that interpret the scene according to the current task at hand. Attention has been suggested to play an important role in the process of scene understanding by prioritizing relevant information. However, the underlying processes that allow cognition to guide vision have not been fully explored. Our procedure has its origin in current findings of research in attention. We suggest an approach in which high-level cognitive processes are top-down directed and modulate stimulus signals such that vision is a constructive process in time. Prior knowledge is combined with the observation taken from the image by a population-based inference in order to dynamically update the conspicuity of each feature. Any decision, such as object detection, is based on these distributed conspicuities. We demonstrate this concept on a goal-directed object detection task in natural scenes. (c) 2005 Elsevier Inc. All rights reserved.
机译:视频监控和视觉引导机器人等技术需要灵活的视觉系统,这些视觉系统可以根据当前的任务来解释场景。已经建议通过优先安排相关信息在场景理解过程中发挥重要作用。但是,尚未充分探讨允许认知引导视觉的基本过程。我们的程序起源于当前受到关注的研究结果。我们建议一种方法,其中高水平的认知过程是自上而下的,并调节刺激信号,从而使视觉成为及时的建设性过程。先验知识与基于总体的推断从图像中获取的观察相结合,以便动态更新每个特征的醒目性。任何决策(例如对象检测)都是基于这些分布的显着性。我们在自然场景中的目标导向物体检测任务中演示了此概念。 (c)2005 Elsevier Inc.保留所有权利。

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