Modeling direction selective visual neural network with ON and OFF pathways for extracting motion cues from cluttered background

Fu, Qinbing and Yue, Shigang (2017) Modeling direction selective visual neural network with ON and OFF pathways for extracting motion cues from cluttered background. In: The 2017 International Joint Conference on Neural Networks (IJCNN 2017), 14 - 19 May 2017, Alaska.

PID4658843.pdf - Whole Document

Item Type:Conference or Workshop contribution (Paper)
Item Status:Live Archive


The nature endows animals robustvision systems for extracting and recognizing differentmotion cues, detectingpredators, chasing preys/mates in dynamic and cluttered environments. Direction selective neurons (DSNs), with preference to certain orientation visual stimulus, have been found in both vertebrates and invertebrates for decades. In thispaper, with respectto recent biological research progress in motion-detecting circuitry, we propose a novel way to model DSNs for recognizing movements on four cardinal directions. It is based on an architecture of ON and OFF visual pathways underlies a theory of splitting motion signals into parallel channels, encoding brightness increments and decrements separately. To enhance the edge selectivity and speed response to moving objects, we put forth a bio-plausible spatial-temporal network structure with multiple connections of same polarity ON/OFF cells. Each pair-wised combination is filtered with dynamic delay depending on sampling distance. The proposed vision system was challenged against image streams from both synthetic and cluttered real physical scenarios. The results demonstrated three major contributions: first, the neural network fulfilled the characteristics of a postulated physiological map of conveying visual information through different neuropile layers; second, the DSNs model can extract useful directional motion cues from cluttered background robustly and timely, which hits at potential of quick implementation in visionbased micro mobile robots; moreover, it also represents better speed response compared to a state-of-the-art elementary motion detector.

Keywords:diretion selective neurons, ON and OFF visual pathways, cluttered background, useful motion cues, Reichardt detectors, spatio-temporal
Subjects:G Mathematical and Computer Sciences > G400 Computer Science
G Mathematical and Computer Sciences > G740 Computer Vision
Divisions:College of Science > School of Computer Science
Related URLs:
ID Code:26619
Deposited On:04 Mar 2017 22:41

Repository Staff Only: item control page