DocumentCode :
48855
Title :
Retinomorphic Event-Based Vision Sensors: Bioinspired Cameras With Spiking Output
Author :
Posch, Christoph ; Serrano-Gotarredona, T. ; Linares-Barranco, B. ; Delbruck, Tobi
Author_Institution :
Inst. de la Vision, Univ. Pierre at Marie Curie, Paris, France
Volume :
102
Issue :
10
fYear :
2014
fDate :
Oct. 2014
Firstpage :
1470
Lastpage :
1484
Abstract :
State-of-the-art image sensors suffer from significant limitations imposed by their very principle of operation. These sensors acquire the visual information as a series of “snapshot” images, recorded at discrete points in time. Visual information gets time quantized at a predetermined frame rate which has no relation to the dynamics present in the scene. Furthermore, each recorded frame conveys the information from all pixels, regardless of whether this information, or a part of it, has changed since the last frame had been acquired. This acquisition method limits the temporal resolution, potentially missing important information, and leads to redundancy in the recorded image data, unnecessarily inflating data rate and volume. Biology is leading the way to a more efficient style of image acquisition. Biological vision systems are driven by events happening within the scene in view, and not, like image sensors, by artificially created timing and control signals. Translating the frameless paradigm of biological vision to artificial imaging systems implies that control over the acquisition of visual information is no longer being imposed externally to an array of pixels but the decision making is transferred to the single pixel that handles its own information individually. In this paper, recent developments in bioinspired, neuromorphic optical sensing and artificial vision are presented and discussed. It is suggested that bioinspired vision systems have the potential to outperform conventional, frame-based vision systems in many application fields and to establish new benchmarks in terms of redundancy suppression and data compression, dynamic range, temporal resolution, and power efficiency. Demanding vision tasks such as real-time 3-D mapping, complex multiobject tracking, or fast visual feedback loops for sensory-motor action, tasks that often pose severe, sometimes insurmountable, challenges to conventional artificial vision systems, are in reach - sing bioinspired vision sensing and processing techniques.
Keywords :
cameras; data compression; image resolution; image sensors; optical sensors; 3D mapping; artificial imaging system; artificial vision sensing; bioinspired camera; bioinspired neuromorphic optical sensing; biological vision system; complex multiobject tracking; data compression; decision making; fast visual feedback loop; frame-based vision system; image acquisition; image data recording; image sensor; retinomorphic event-based vision sensor; sensory-motor action; snapshot image series; temporal resolution; Biosensors; Cameras; Event recognition; Image sensors; Neuromorphic engineering; Neuromorphics; Photoreceptors; Retina; Time-domain anlaysis; Visualization; Address–event representation (AER); Address??event representation (AER); biomimetics; complementary metal–oxide–semiconductor (CMOS) image sensors; complementary metal??oxide??semiconductor (CMOS) image sensors; event-based vision; focal-plane processing; high dynamic range (HDR); neuromorphic electronics; neuromorphic engineering; silicon retina; time-domain correlated double sampling (TCDS); time-domain imaging; video compression;
fLanguage :
English
Journal_Title :
Proceedings of the IEEE
Publisher :
ieee
ISSN :
0018-9219
Type :
jour
DOI :
10.1109/JPROC.2014.2346153
Filename :
6887319
Link To Document :
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