RGB-D Fusion: Real-time Robust Tracking and Dense Mapping with RGB-D Data Fusion

Title
RGB-D Fusion: Real-time Robust Tracking and Dense Mapping with RGB-D Data Fusion
Authors
이성오임화섭김형곤안상철
Keywords
3D Modeling; 3D Reconstruction
Issue Date
2014-09
Publisher
IROS (IEEE/RSJ International Conference on Intelligent Robots and Systems)
Citation
, 2749-2754
Abstract
We present RGB-D Fusion, a framework which robustly tracks and reconstructs dense textured surfaces of scenes and objects by integrating both color and depth images streamed from a RGB-D sensor into a global colored volume in real-time. To handle failure of the ICP-based tracking approach, KinectFusion, due to the lack of sufficient geometric information, we propose a novel approach which registers the input RGB-D image with the colored volume by photometric tracking and geometric alignment. We demonstrate the strengths of the proposed approach compared with the ICP-based approach and show superior performance of our algorithm with real-world data.
URI
http://pubs.kist.re.kr/handle/201004/48166
Appears in Collections:
KIST Publication > Conference Paper
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