TY - JOUR
T1 - Neuromorphic implementation of motion detection using oscillation interference
AU - Tsur, Elishai Ezra
AU - Rivlin-Etzion, Michal
N1 - Publisher Copyright:
© 2019
PY - 2020/1/21
Y1 - 2020/1/21
N2 - Motion detection is paramount for computational vision processing. This is however a particularly challenging task for a neuromorphic hardware in which algorithms are based on interconnected spiking entities, as the instantaneous visual stimuli reports merely on luminance change. Here we describe a neuromorphic algorithm, in which an array of neuro-oscillators is utilized to detect motion and its direction over an entire field of view. These oscillators are induced via phase shifted Gabor functions, allowing them to oscillate in response to motion in one predefined direction, and to dump to zero otherwise. We developed the algorithm using the Neural Engineering Framework (NEF), making it applicable for a variety of neuromorphic hardware. Our algorithm extends the existing growing set of approaches aiming at utilizing neuromorphic hardware for vision processing, which enable to minimize energy exploitation and silicon area while enhancing computational capabilities.
AB - Motion detection is paramount for computational vision processing. This is however a particularly challenging task for a neuromorphic hardware in which algorithms are based on interconnected spiking entities, as the instantaneous visual stimuli reports merely on luminance change. Here we describe a neuromorphic algorithm, in which an array of neuro-oscillators is utilized to detect motion and its direction over an entire field of view. These oscillators are induced via phase shifted Gabor functions, allowing them to oscillate in response to motion in one predefined direction, and to dump to zero otherwise. We developed the algorithm using the Neural Engineering Framework (NEF), making it applicable for a variety of neuromorphic hardware. Our algorithm extends the existing growing set of approaches aiming at utilizing neuromorphic hardware for vision processing, which enable to minimize energy exploitation and silicon area while enhancing computational capabilities.
KW - Motion detection
KW - Nengo
KW - Neural engineering framework
KW - Neuromorphic vision sensor
KW - Optical flow
KW - Spike-based camera emulator
UR - http://www.scopus.com/inward/record.url?scp=85072769487&partnerID=8YFLogxK
U2 - 10.1016/j.neucom.2019.09.072
DO - 10.1016/j.neucom.2019.09.072
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AN - SCOPUS:85072769487
SN - 0925-2312
VL - 374
SP - 54
EP - 63
JO - Neurocomputing
JF - Neurocomputing
ER -