An oscillatory correlation model of object-based attention

Marcos G. Quiles, DeLiang Wang, Liang Zhao, Roseli A. F. Romero, De-Shuang Huang
2009 2009 International Joint Conference on Neural Networks  
Attention is a critical mechanism for visual scene analysis. By means of attention, it is possible to break down the analysis of a complex scene to the analysis of its parts through a selection process. Empirical studies demonstrate that attentional selection is conducted on visual objects as a whole. We present a neurocomputational model of object-based selection in the framework of oscillatory correlation. By segmenting an input scene and integrating the segments with their conspicuity
more » ... d from a saliency map, the model selects salient objects rather than salient locations. The proposed system is composed of three modules: a saliency map providing saliency values of image locations, image segmentation for breaking the input scene into a set of objects, and object selection which allows one of the objects of the scene to be selected at a time. This object selection system has been applied to real images and the simulation results show its effectiveness.
doi:10.1109/ijcnn.2009.5178597 dblp:conf/ijcnn/QuilesWZRH09 fatcat:yqskf4v3lvfn5gfl64hbhqz7w4