Object Detection Based on Saliency Map Using Reference Image Containing Complex Background

We propose an object detection method based on a saliency map using a reference image containing complex background for service robots. In previous detection methods, images that the user prepares in advance contain mostly simple background. However, in order to make robots perform daily tasks, the robots should be able to detect an object using snapshots that contain a complex background. In order to decrease the effect of features in the background, our proposed method classifies local features based on saliency from images. This paper shows the efficacy of the proposed method; furthermore, we demonstrate that our service robot detects certain objects according to the proposed method.