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Indoor environment recognition based on depth image

깊이 영상 기반 실내 공간 인식

  • Received : 2014.09.19
  • Accepted : 2014.10.24
  • Published : 2014.11.29

Abstract

In this paper, we propose a method using an image received by the depth camera in order to separate the wall in a three-dimensional space indoor environment. Results of the paper may be used to provide valuable information on the three-dimensional space. For example, they may be used to recognize the indoor space, to detect adjacent objects, or to project a projector on the wall. The proposed method first detects a normal vector at each point by using the three dimensional coordinates of points. The normal vectors are then clustered into several groups according to similarity. The RANSAC algorithm is applied to separate out planes. The domain knowledge helps to determine the wall among planes in an indoor environment. This paper concludes with experimental results that show performance of the proposed method in various experimental environment.

본 논문에서는 실내 환경의 3차원 공간에서 벽면을 분리해내기 위해 깊이 카메라로 받아들인 영상을 이용한 방법을 제안한다. 논문의 실험 결과에서 얻을 수 있는 정보를 이용하면 실내 공간을 인식하거나 그에 따른 인접한 물체의 탐색 또는 벽면에 프로젝터를 투사하는 등 3차원 공간 활용에 용이하다. 논문에서 제안하는 방법은 먼저 3차원 입력 영상에서의 좌표 점들을 이용하여 법선 벡터를 검출하고, 검출 된 법선 벡터를 비슷한 벡터들끼리의 그룹으로 나눈다. 나누어진 그룹들을 RANSAC을 이용하여 평면 단위로 분리한 후, 분리된 평면들은 실내 환경에서 알 수 있는 도메인 지식들에 기반 하여 벽면으로 구분 된다. 마지막으로 본 논문에서 제안하는 방법은 다양한 실험 환경을 통해 성능을 입증한다.

Keywords

References

  1. Illingworth, John, and Josef Kittler. "A survey of the Hough transform." Computer vision, graphics, and image processing, Vol. 44, No. 1, pp. 87-116, Oct. 1988. https://doi.org/10.1016/S0734-189X(88)80033-1
  2. Fischler, Martin A., and Robert C. Bolles. "Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography." Communications of the ACM, Vol. 24, No. 6, pp. 381-395, Jun, 1981. https://doi.org/10.1145/358669.358692
  3. Borrmann, D., Elseberg, J., Lingemann, K., & Nuchter, A. "The 3D Hough Transform for plane detection in point clouds: A review and a new accumulator design", 3D Research, Vol. 2, No. 2, pp. 1-13, Jan. 2011.
  4. Dong-joong Kang, "A Stereo Camera Based Method of Plane Detection for Path Finding of Walking Robot", Journal of institute of control robotics and systems, Vol. 14, No. 3, pp. 236-241, Mar. 2008. https://doi.org/10.5302/J.ICROS.2008.14.3.236
  5. Pitas, I. "Digital Image Processing Algorithms", Prentice Hall, 1993.
  6. Atid Shamaie and Alistair Sutherland, "A Dynamic Model for Real-Time Tracking of Hands in Bimanual Movements" GW2003, LNAI 2915, pp. 172-179, 2004.
  7. RANSAC algorithm, http://www.mrpt.org/tutorials/programming/maths-and-geometry/ransac-c-examples/
  8. Holz, D., Holzer, S., Rusu, R. B., & Behnke, S. "Real-time plane segmentation using RGB-D cameras" In RoboCup 2011: Robot Soccer World Cup XV, pp. 306-317, 2012.
  9. Sung-il Joo, Sun-hee Weon, Hyung-il Choi, "3D Pointing for Effective Hand Mouse in Depth Image", Journal of The Korea Society of Computer and Information, Vol. 19, No. 8, pp. 35-44, Aug. 2014. https://doi.org/10.9708/jksci.2014.19.8.035