Lee, Seong-Oh Lim, Hwasup Kim, Hyoung-Gon Ahn, Sang Chul 2024-01-19T12:08:36Z 2024-01-19T12:08:36Z 2022-03-07 2014-09 2153-0858 https://pubs.kist.re.kr/handle/201004/115385 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. English IEEE RGB-D Fusion: Real-time Robust Tracking and Dense Mapping with RGB-D Data Fusion Conference 1 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp.2749 - 2754 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2749 2754 US Chicago, IL 2014-09-14 2014 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS 2014) 000349834602127 2-s2.0-84911476724