A computational cognition model of perception, memory, and judgment

被引：0
作者：
XiaoLan Fu
LianHong Cai
Ye Liu
Jia Jia
WenFeng Chen
Zhang Yi
GuoZhen Zhao
YongJin Liu
ChangXu Wu
机构：
[1] Chinese Academy of Sciences,State Key Laboratory of Brain and Cognitive Science, Institute of Psychology
[2] Tsinghua University,TNLIST, Department of Computer Science and Technology
[3] Sichuan University,College of Computer Science
[4] Chinese Academy of Sciences,Key Laboratory of Behavioral Science, Institute of Psychology
来源：
Science China Information Sciences | 2014年 / 57卷
关键词：
perception; memory; judgment; computational cognition model;
D O I：
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中图分类号：
学科分类号：
摘要：
The mechanism of human cognition and its computability provide an important theoretical foundation to intelligent computation of visual media. This paper focuses on the intelligent processing of massive data of visual media and its corresponding processes of perception, memory, and judgment in cognition. In particular, both the human cognitive mechanism and cognitive computability of visual media are investigated in this paper at the following three levels: neurophysiology, cognitive psychology, and computational modeling. A computational cognition model of Perception, Memory, and Judgment (PMJ model for short) is proposed, which consists of three stages and three pathways by integrating the cognitive mechanism and computability aspects in a unified framework. Finally, this paper illustrates the applications of the proposed PMJ model in five visual media research areas. As demonstrated by these applications, the PMJ model sheds some light on the intelligent processing of visual media, and it would be innovative for researchers to apply human cognitive mechanism to computer science.
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页码：1 / 15
页数：14
相关论文
共 203 条
  • [1] Hu S M(2013)Internet visual media processing: a survey with graphics and vision applications Vis Comput 29 393-405
  • [2] Chen T(2011)Maintaining frame rate perception in interactive environments by exploiting audio-visual cross-modal interaction Vis Comput 27 57-66
  • [3] Xu K(2012)Using normalized compression distance for image similarity measurement: an experimental study Vis Comput 28 1063-1084
  • [4] Hulusic V(2000)Computational neuroscience at the NIH Nat Neurosci 3 1161-1164
  • [5] Debattista K(2007)Top-down versus bottom-up control of attention in the prefrontal and posterior parietal cortices Science 315 1860-1862
  • [6] Aggarwal V(2007)Search goal tunes visual features optimally Neuron 53 605-617
  • [7] Vazquez P-P(2012)Early involvement of prefrontal cortex in visual bottom-up attention Nat Neurosci 15 1160-1166
  • [8] Marco J(2002)Control of goal-directed and stimulus-driven attention in the brain Nat Rev Neurosci 3 201-215
  • [9] Buschman T J(2011)Causal role of the prefrontal cortex in top-down modulation of visual processing and working memory Nat Neurosci 14 656-661
  • [10] Miller E K(1999)Top-down signal from prefrontal cortex in executive control of memory retrieval Nature 401 699-703
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