Recent Advances in Bio-Inspired Vision Sensor: A Review

被引:0
|
作者
Zhong, Xiaoyu [1 ]
Yu, Zhiguo [1 ]
Gu, Xiaofeng [1 ]
机构
[1] Jiangnan Univ, Dept Elect Engn, Wuxi 214122, Peoples R China
关键词
Event-based cameras; biologically inspired visual sensors; high temporal resolution; low latency; high dynamic range; robotics and computer vision; IMAGE-RECONSTRUCTION; EVENT; DRIVEN; PIXEL; SLAM; TRACKING; PAIR;
D O I
10.1142/S0218126624300083
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Event-based cameras, also known as biologically inspired visual sensors, are capable of capturing real-time scene changes efficiently. Unlike traditional frame-based cameras, event cameras solely report triggered pixel-level brightness changes which are referred to as events. Event-based cameras show many advantages such as high temporal resolution, low latency, and high dynamic range, making them very attractive in robotics and computer vision, especially in challenging scenarios that are too demanding for traditional cameras. In this paper, we provide a comprehensive overview of the emerging field of event-based vision, focusing on the operation principle, sampling mechanisms, and algorithms that take advantage of their superior features. We also delve into the various tasks for which event cameras are utilized, such as object tracking, optical flow estimation, 3D reconstruction, SLAM, image reconstruction, and recognition. Additionally, we highlight the challenges and future opportunities for event cameras, seeking a more efficient way for machines to perceive and interact with the world.
引用
收藏
页数:43
相关论文
共 50 条
  • [31] Bio-inspired microfluidics: A review
    Raj, Kiran M.
    Priyadarshani, Jyotsana
    Karan, Pratyaksh
    Bandyopadhyay, Saumyadwip
    Bhattacharya, Soumya
    Chakraborty, Suman
    BIOMICROFLUIDICS, 2023, 17 (05)
  • [32] Recent advances in evolutionary and bio-inspired adaptive robotics: Exploiting embodied dynamics
    Phil Husbands
    Yoonsik Shim
    Michael Garvie
    Alex Dewar
    Norbert Domcsek
    Paul Graham
    James Knight
    Thomas Nowotny
    Andrew Philippides
    Applied Intelligence, 2021, 51 : 6467 - 6496
  • [33] Bio-inspired sensor network design
    Barbarossa, Sergio
    Scutari, Gesualdo
    IEEE SIGNAL PROCESSING MAGAZINE, 2007, 24 (03) : 26 - 35
  • [34] Bio-inspired Asynchronous Pixel Event Tri-color Vision Sensor
    Lenero-Bardallo, Juan A.
    Bryn, D. H.
    Hafliger, P.
    2011 IEEE BIOMEDICAL CIRCUITS AND SYSTEMS CONFERENCE (BIOCAS), 2011, : 253 - 256
  • [35] Special Issue on Bio-inspired Vision Systems
    Zillich, Michael
    Kruger, Norbert
    KUNSTLICHE INTELLIGENZ, 2015, 29 (01): : 5 - 7
  • [36] Special Issue on Bio-inspired Vision Systems
    Michael Zillich
    Norbert Krüger
    KI - Künstliche Intelligenz, 2015, 29 (1) : 5 - 7
  • [37] Bio-inspired image processing for vision aids
    Morillas, C.
    Pelayo, F.
    Cobos, J. P.
    Prieto, A.
    Romero, S.
    BIOSIGNALS 2008: PROCEEDINGS OF THE FIRST INTERNATIONAL CONFERENCE ON BIO-INSPIRED SYSTEMS AND SIGNAL PROCESSING, VOL II, 2008, : 63 - 69
  • [38] Bio-inspired Active Vision for Obstacle Avoidance
    Chessa, Manuela
    Murgia, Saverio
    Nardelli, Luca
    Sabatini, Silvio P.
    Solari, Fabio
    2014 PROCEEDINGS OF THE 9TH INTERNATIONAL CONFERENCE ON COMPUTER GRAPHICS THEORY AND APPLICATIONS (GRAPP 2014), 2014, : 505 - 512
  • [39] GPU Implementation of a Bio-inspired Vision Model
    Urena, Raquel
    Morillas, Christian
    Romero, Samuel
    Pelayo, Francisco J.
    ADVANCES IN COMPUTATIONAL INTELLIGENCE, IWANN 2011, PT I, 2011, 6691 : 417 - 424
  • [40] Advances in bio-inspired computing: Techniques and applications
    Jain, L. C.
    Lim, C. P.
    NEUROCOMPUTING, 2014, 125 : 183 - 183