Motion perception based on ON/OFF channels: A survey

被引:9
|
作者
Fu, Qinbing [1 ]
机构
[1] Guangzhou Univ, Machine Life & Intelligence Res Ctr, Sch Math & Informat Sci, Guangzhou 510006, Peoples R China
基金
中国国家自然科学基金;
关键词
Motion perception; ON; OFF channels; Selectivity; Neural modelling; Bio-inspired sensor; Machine application; ON-OFF UNITS; ORTHOPTERAN DCMD NEURON; 1ST OPTIC CHIASM; VISUAL-MOTION; COMPUTATIONAL STRUCTURE; DIRECTION SELECTIVITY; COLLISION DETECTION; DETECTION CIRCUITS; LOOMING DETECTION; RECEPTIVE-FIELDS;
D O I
10.1016/j.neunet.2023.05.031
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Motion perception is an essential ability for animals and artificially intelligent systems interacting effectively, safely with surrounding objects and environments. Biological visual systems, that have naturally evolved over hundreds-million years, are quite efficient and robust for motion perception, whereas artificial vision systems are far from such capability. This paper argues that the gap can be significantly reduced by formulation of ON/OFF channels in motion perception models encoding luminance increment (ON) and decrement (OFF) responses within receptive field, separately. Such signal-bifurcating structure has been found in neural systems of many animal species articulating early motion is split and processed in segregated pathways. However, the corresponding biological substrates, and the necessity for artificial vision systems have never been elucidated together, leaving concerns on uniqueness and advantages of ON/OFF channels upon building dynamic vision systems to address real world challenges. This paper highlights the importance of ON/OFF channels in motion perception through surveying current progress covering both neuroscience and computationally modelling works with applications. Compared to related literature, this paper for the first time provides insights into implementation of different selectivity to directional motion of looming, translating, and small-sized target movement based on ON/OFF channels in keeping with soundness and robustness of biological principles. Existing challenges and future trends of such bio-plausible computational structure for visual perception in connection with hotspots of machine learning, advanced vision sensors like event-driven camera finally are discussed. (c) 2023 Elsevier Ltd. All rights reserved.
引用
收藏
页码:1 / 18
页数:18
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