Computer Science ›› 2025, Vol. 52 ›› Issue (7): 170-188.doi: 10.11896/jsjkx.240400209

• Computer Graphics & Multimedia • Previous Articles     Next Articles

Bio-inspired Neural Network with Visual Invariant Response to Moving Pedestrian

YU Shihai1,2, HU Bin1,2,3   

  1. 1 State Key Laboratory of Public Big Data, College of Computer Science and Technology, Guizhou University, Guiyang 550025, China
    2 College of Computer Science and Technology, Guizhou University, Guiyang 550025, China
    3 Artificial Intelligence Research Institute, Guizhou University, Guiyang 550025, China
  • Received:2024-04-30 Revised:2024-09-08 Published:2025-07-17
  • About author:YU Shihai,born in 1997,postgraduate.His main research interests include computer intelligence and computer vision.
    HU Bin,born in 1977,Ph.D,professor,Ph.D supervisor,is a senior member of CCF(No.F8648S).His main research interests include computer intelligence,neural computing,computer vision and artificial intelligence.
  • Supported by:
    National Natural Science Foundation of China(62066006),Natural Science Foundation of Guizhou Province,China(QKHJC[2020]1Y261,QKHJC[2019]1178) and Scientific Research Project for the Introduced Talents of Guizhou University(GDRJHZ(2019)58).

Abstract: Visual invariance is a cardinal neural tuning response for the cognitive function in biological vision-brain systems,but no computational model has been reported for one such issue to the moving pedestrian vision perception.To fill this gap,a bio-inspired artificial visual neural network(mpvirNN) with visual invariant response to moving pedestrian perception is investigated,based on the current researches revealed by biological studies,including the structural properties of mammalian retina,the spiking response mechanism of neurons in the medial temporal lobe area(MTL) of the human brain,and the kinetics properties of human.The proposed neural network consists of two count-parts:presynaptic network and postsynaptic network.The presynaptic network captures low-order visual motion information of pedestrian objects in the field of view,by means of the visual information processing mechanism in mammalian retina.The postsynaptic network extracts visual cues of pedestrian motion frequency properties,and integrates them to generate the neural membrane potential clusters against to the object in the field of view.Systematic experimental studies show that mpvirNN can effectively perceive moving pedestrian in different visual scenes and tune neural spike response with visual invariance properties.This work is involved in the processing of visual dynamic information inspired by biological vision-brain systems,which can contribute some new ideas and methods for pedestrian detection and cognitive recognition research in artificial intelligence.

Key words: Visual invariance, Neural spiking response, Human kinetics property, Moving pedestrian, Retinal nerve, Visual motion perception

CLC Number: 

  • TP183
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