Approach for Object Recognition Based on a Computational Model of Feature Binding
一种基于特征捆绑计算模型的物体识别方法

This paper proposes a novel method for object recognition by using a computational model of feature binding, in which Gabor features are employed as the elementary features and correlation statistics provide the basis for implementing the feature binding. A group of object recognition experiments are conducted with this method,and the results prove the comparatively good performances with high recognition precision and high speed,indicating the validity of this method and the computational model.