Three-dimensional scene reconstruction using multiview images and depth camera

Abstract

This paper presents a novel multi-depth map fusion approach for the 3D scene reconstruction. Traditional stereo matching techniques that estimate disparities between two images often produce inaccurate depth map because of occlusion and homogeneous area. On the other hand, Depth map obtained from the depth camera is globally accurate but noisy and provides a limited depth range. In order to compensate pros and cons of these two methods, we propose a depth map fusion method that fuses the multi-depth maps from stereo matching and the depth camera. Using a 3-view camera system that includes a depth camera for the center-view, we first obtain 3-view images and a depth map from the center-view depth camera. Then we calculate camera parameters by camera calibration. Using the camera parameters, we rectify left and right-view images with respect to the center-view image for satisfying the well-known epipolar constraint. Using the center-view image as a reference, we obtain two depth maps by stereo matching between the center-left image pair and the center-right image pair. After preprocessing each depth map, we pick an appropriate depth value for each pixel from the processed depth maps based on the depth reliability. Simulation results obtained by our proposed method showed improvements in some background regions.