计算机科学

计算机科学 ›› 2025, Vol. 52 ›› Issue (7): 170-188.doi: 10.11896/jsjkx.240400209

• 计算机图形学&多媒体 • 上一篇    下一篇

生物启发的运动行人视觉不变性响应神经网络

于世海1,2, 胡滨1,2,3   

  1. 1 贵州大学计算机科学与技术学院公共大数据国家重点实验室 贵阳 550025
    2 贵州大学计算机科学与技术学院 贵阳 550025
    3 贵州大学人工智能研究院 贵阳 550025
  • 收稿日期:2024-04-30 修回日期:2024-09-08 发布日期:2025-07-17
  • 通讯作者: 胡滨(bhu1@gzu.edu.cn)
  • 作者简介:(834250889@qq.com)
  • 基金资助:
    国家自然科学基金(62066006);贵州省自然科学基金(黔科合基础[2020]1Y261,黔科合基础[2019]1178);贵州大学引进人才科研项目(贵大人基合字(2019)58号)

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).

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摘要： 视觉不变性是生物视脑认知机能的重要神经调谐响应特性,但目前还尚无关于该神经特性在运动行人视觉感知问题研究中的计算模型。针对该问题,基于哺乳动物视觉神经结构特性,借助人类大脑内侧颞叶区(MTL)神经元尖峰响应机理以及人体运动力学特性,提出一种适用于运动行人视觉感知与不变性响应的人工视觉神经网络(mpvirNN)。所提出的神经网络包括两个部分:突触前网络和突触后网络。突触前网络基于哺乳动物视网膜视觉信息加工处理机制,感知视野域中行人对象的低阶视觉运动信息;突触后网络提取行人运动周期频率视觉线索,整合输出表征视觉响应的神经膜电位簇。系统性的实验研究表明,mpvirNN能有效感知视觉场景中的运动行人对象,产生具有视觉不变性特性的神经尖峰响应输出。研究涉及生物视脑认知神经机制启发的运动行人视觉动态信息加工处理,可为人工智能中的行人检测与认知识别研究提供新思想、新方法。

关键词: 视觉不变性, 神经尖峰响应, 人体运动力学特性, 运动行人, 视网膜神经, 视觉运动感知

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

中图分类号: 

  • TP183
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