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Cognitive aspects of multiple tasks and perception: Overview and discussion on recent studies

机译:多项任务和知觉的认知方面:概述和讨论最近的研究

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Cognitive aspects implemented in computational processes establish frames to model human actions relative to the human corresponding senses. Vision is one of them. To conceive appropriated artificial architectures, behavior manifestations and brain structural proprieties are intensively studied. Physiology is modeled in simplified schemas in order to be implemented in virtual systems and machine models. Eye tracking models offer clues for implementing artificial vision on robots, to give salient information for marketing, for art, or forensic research. If the task might be relatively simple for following one precise target in an image, the issues are more complicated when more objects have to be identified, in a multitask perception simulation. Another aspect is to take into consideration the semantic content and this depends on the detailed, rule-frames, formulation of the problem. A number of direct and reverse processes are identified: from real image to human vision and understanding, and from observation of the human behavior, to computer modeling and image processing. The paper makes a quick overview on the relevant studies connected to these topics and proposes a new schema to identify salient points in an image, based both on image processing techniques and on cognitive aspects, mainly from vision and multi-task perception studies.
机译:计算过程中实施的认知方面建立相对于人类对应的感官来建立模拟人类动作的帧。愿景是其中之一。为了构思占用的人工架构,行为表现形式和脑结构专题都是深入研究。生理学以简化的模式建模,以便在虚拟系统和机器模型中实现。眼睛跟踪模型提供了在机器人上实施人为视觉的线索,为艺术或法医研究提供营销的突出信息。如果在图像中遵循一个精确的目标时,任务可能相对简单,则在多任务感知仿真中必须识别更多对象时,问题更加复杂。另一方面是考虑语义内容,这取决于详细的规则帧,对问题的制定。鉴定了许多直接和逆向过程:从真实的图像到人类视觉和理解,并从人类行为观察到计算机建模和图像处理。本文快速概述了与这些主题相关的相关研究,并提出了一种新的架构,以确定图像中的突出点,主要是在图像处理技术和认知方面,主要来自视觉和多任务的感知研究。

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