학술논문

Hybrid Kinect Depth Map Refinement for Transparent Objects
Document Type
Conference
Source
2014 22nd International Conference on Pattern Recognition Pattern Recognition (ICPR), 2014 22nd International Conference on. :2751-2756 Aug, 2014
Subject
Computing and Processing
Estimation
Cameras
Sensors
Accuracy
Three-dimensional displays
Inference algorithms
Surface reconstruction
Language
ISSN
1051-4651
Abstract
Depth sensors such as Kinect fail to find the depth of transparent objects which makes 3D reconstruction of such objects a challenge. The refinement algorithms for Kinect depth maps either do not address transparency or they only provide sparse depth on such objects which is inadequate for dense 3D reconstruction. In order to solve this problem, we propose a fully-connected CRF based hybrid refinement algorithm. We incorporate stereo cues from cross-modal stereo between IR and RGB cameras of the Kinect and Kinect's depth map. Our algorithm does not require any additional cameras and still provides dense depth estimations of transparent objects and specular surfaces with high accuracy.