Object recognition based on inhibition-of-return control using particle filter

We propose an object recognition method based on a saliency using a reference video containing complex background for service robots. In previous object recognition methods, in training phase, images that the user prepares contain mostly simple background. However, in order to make robots perform daily tasks, the robots should be able to recognition an object using teaching scene that contain complex backgrounds. In order to decrease the effect of features in the background, our proposed method classifies local features based on saliency from video images. This paper shows the efficacy of the proposed method; furthermore, we demonstrate that our proposed method recognizes certain objects.