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학술대회 Biologically Inspired Computational Models of Visual Attention for Personalized Autonomous Agents: A Survey
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저자
문진영, 이형직, 배창석
발행일
201110
출처
International Conference on Information Technology Convergence and Services (ITCS) / FTRA International Conference on Intelligent Robotics, Automations, Telecommunication Facilities, and Applications (IRoA) 2011 (LNEE 107), v.107, pp.547-555
DOI
https://dx.doi.org/10.1007/978-94-007-2598-0_58
협약과제
10SC1800, 인간 교감 신개념 UI 기반 인터랙션 기술, 손승원
초록
Perception is one of essential capabilities for personalized autonomous agents that act like their users without intervention of the users in order to understand the environment for themselves like a human being. Visual perception in humans plays a major role to interact with objects or entities within the environment by interpreting their visual sensing information. The major technical obstacle of visual perception is to efficiently process enormous amount of visual stimuli in real-time. Therefore, computational models of visual attention that decide where to focus in the scene have been proposed to reduce the visual processing load by mimicking human visual system. This chapter provides the background knowledge of cognitive theories that the models were founded on and analyzes the computational models necessary to build a personalized autonomous agent that acts like a specific person as well as typical human beings. © 2011 Springer Science+Business Media B.V.
KSP 제안 키워드
Cognitive theories, Computational Model, Human Visual System(HVS), Processing load, Real-Time, Visual Perception, autonomous agent, background knowledge, biologically inspired, human being, visual attention