The Journal of Korea Robotics Society (로봇학회논문지)

Korea Robotics Society (한국로봇학회)
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Refinements of Multi-sensor based 3D Reconstruction using a Multi-sensor Fusion Disparity Map

다중센서 융합 상이 지도를 통한 다중센서 기반 3차원 복원 결과 개선

  • 김시종 (한국과학기술원 전기 및 전자공학과) ;
  • 안광호 (한국과학기술원 전기 및 전자공학과) ;
  • 성창훈 (한국과학기술원 전기 및 전자공학과) ;
  • 정명진 (한국과학기술원 전기 및 전자공학과)
  • Received : 2009.09.28
  • Accepted : 2009.11.24
  • Published : 2009.11.30
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Abstract

This paper describes an algorithm that improves 3D reconstruction result using a multi-sensor fusion disparity map. We can project LRF (Laser Range Finder) 3D points onto image pixel coordinatesusing extrinsic calibration matrixes of a camera-LRF (${\Phi}$, ${\Delta}$) and a camera calibration matrix (K). The LRF disparity map can be generated by interpolating projected LRF points. In the stereo reconstruction, we can compensate invalid points caused by repeated pattern and textureless region using the LRF disparity map. The result disparity map of compensation process is the multi-sensor fusion disparity map. We can refine the multi-sensor 3D reconstruction based on stereo vision and LRF using the multi-sensor fusion disparity map. The refinement algorithm of multi-sensor based 3D reconstruction is specified in four subsections dealing with virtual LRF stereo image generation, LRF disparity map generation, multi-sensor fusion disparity map generation, and 3D reconstruction process. It has been tested by synchronized stereo image pair and LRF 3D scan data.

Keywords

References

  1. Alastair Harrison and Paul Newman, "High Quality 3D Laser Ranging Under General Vehicle Motion," IEEE International Conference on Robotics and Automation, 2008.
  2. Heiko Hirschmuller, Peter R. Innocent and Jon Garibaldi, "Real-Time Correlation-Based Stereo Vision with Reduced Border Errors," International Journal of computer Vision, Vol.47, 2002.
  3. Kiana Hajebi, John X. Zelek, "Dense Surface from Infrared Stereo," IEEE Workshop on Applications of Computer Vision, 2007.
  4. J. H. Joung, K. H. An, J.W. Kang, W. H. Kim, W. H. Kim, and M. J. Chung, "3D terrain Reconstruction Using 2D Laser Range Finder and Camera Based on Cubic Grid," International Conference on Ubiquitous Robots and Ambient Intelligence, 2008.
  5. Z. Zhang, "A Flexible New Technique for Camera Calibration," IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol.22, No.11, 2000.
  6. A. Zhang and R. Pless, "Extrinsic Calibration of a Camera and Laser Range Finder (improves camera calibration)," Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2004.