Depth Information Fused Salient Object Detection

Abstract

Saliency Detection has emerged as a hot topic due to its potential application in image and video understanding. Most existing saliency detection algorithms focus on two-dimensional information while the depth information is often ignored. In this paper, we first create the salient object ground truth of a specific image dataset which contains 600 RGB-D (color and depth information) images taken from different surroundings with different angle and intensity of illumination. The depth image describes the depth information of each object in the image from the perspective of a viewer, and the intensity value of every pixel in the depth image denotes the depth information. With the help of depth information, a more precise object description can be acquired. Furthermore, several state-of-the-art saliency detection models can be utilized to generate 2D salient maps, which can be fused with the depth map to detect the salient object in a given image. Experimental results demonstrate the effectiveness of the proposed method.