Visual system based on artificial retina for motion detection.
We present a bioinspired model for detecting spatiotemporal features based on artificial retina response models. Event-driven processing is implemented using four kinds of cells encoding image contrast and temporal information. We have evaluated how the accuracy of motion processing depends on local contrast by using a multiscale and rank-order coding scheme to select the most important cues from retinal inputs. We have also developed some alternatives by integrating temporal feature results and obtained a new improved bioinspired matching algorithm with high stability, low error and low cost. Finally, we define a dynamic and versatile multimodal attention operator with which the system is driven to focus on different target features such as motion, colors, and textures.
Barranco
Francisco
F
Department of Computer Architecture and Technology, University of Granada, 18071 Granada, Spain. fbarranco@atc.ugr.es
Díaz
Javier
J
Ros
Eduardo
E
del Pino
Begoña
B
D000465:Algorithms; D001185:Artificial Intelligence; D003491:Cybernetics / Q000379:methods*; D007089:Image Enhancement / Q000379:methods; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008959:Models, Neurological; D009038:Motion; D012160:Retina / Q000502:physiology*; D013997:Time Factors