Asynchronous Event-Based Motion Processing: From Visual Events to Probabilistic Sensory Representation
| Autor: | Mina A. Khoei, Ryad Benosman, Sio-Hoi Ieng |
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| Rok vydání: | 2019 |
| Předmět: |
Quantitative Biology::Neurons and Cognition
Pixel Computer science Event (computing) business.industry Cognitive Neuroscience Models Neurological Motion Perception ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Probabilistic logic Sensory system Retina Motion (physics) Stimulus modality Arts and Humanities (miscellaneous) Asynchronous communication Humans Computer vision Artificial intelligence business Photic Stimulation Vision Ocular Probability Visual Cortex Biological motion |
| Zdroj: | Neural Computation. 31:1114-1138 |
| ISSN: | 1530-888X 0899-7667 |
| Popis: | In this work, we propose a two-layered descriptive model for motion processing from retina to the cortex, with an event-based input from the asynchronous time-based image sensor (ATIS) camera. Spatial and spatiotemporal filtering of visual scenes by motion energy detectors has been implemented in two steps in a simple layer of a lateral geniculate nucleus model and a set of three-dimensional Gabor kernels, eventually forming a probabilistic population response. The high temporal resolution of independent and asynchronous local sensory pixels from the ATIS provides a realistic stimulation to study biological motion processing, as well as developing bio-inspired motion processors for computer vision applications. Our study combines two significant theories in neuroscience: event-based stimulation and probabilistic sensory representation. We have modeled how this might be done at the vision level, as well as suggesting this framework as a generic computational principle among different sensory modalities. |
| Databáze: | OpenAIRE |
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