Title
A Visual Perceiving And Eyeball-Motion Controlling Neural Network For Object Searching And Locating
Abstract
This paper proposes a visual cognitive neural network for automatic object searching and locating. The model consists of two sub-networks. One is a visual perceiving network, which simulates human eyes to input image signals and recognize an object's direction and distance in terms of a high-level perceiving neuron's maximum response. The other one is an eyeball-motion controlling network, which simulates that human brain's high-level perceiving neurons transfer their responses to eyeball-motion controlling muscle cells to change eye's gaze to the position of the object that the perceiving system is attentive to or interested in. The system is applied to human face features searching and experiments show a promising result.
Year
DOI
Venue
2006
10.1109/IJCNN.2006.247039
2006 IEEE INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORK PROCEEDINGS, VOLS 1-10
Keywords
Field
DocType
muscle cell,visual perception,computer vision,motion control,neural network
Object detection,Computer vision,Motion control,3D single-object recognition,Pattern recognition,Gaze,Computer science,Artificial intelligence,Cognition,Artificial neural network,Visual perception,Form perception
Conference
ISSN
Citations 
PageRank 
2161-4393
4
0.50
References 
Authors
6
4
Name
Order
Citations
PageRank
Jun Miao122022.17
Xilin Chen26291306.27
Wen Gao311374741.77
Yiqiang Chen41446109.32