The paper addresses range image segmentation, particularly of data recorded by range cameras, such as the Microsoft Kinect and the Mesa Swissranger SR4000. These devices record range images at video frame rates and allow for acquisition of 3-dimensional measurement sequences that can be used for 3D reconstruction of indoor environments from moving platforms. The role of segmentation is twofold. First the necessary image co-registration can be based on corresponding segments, instead of corresponding point features (which is common practice currently). Secondly, the segments can be used during subsequent object modelling. By realisising that planar regions in disparity images can be modelled as linear functions of the image coordinates, having integer values for both domain and range, the paper introduces a lookup table based implementation of local Hough transform, allowing to obtain good segmentation results at high speeds.
P. Henry, M. Krainin, E. Herbst, X. Ren and D. Fox, “RGB-D Mapping: Using Kinect-Style Depth Cameras for Dense 3D Modeling of Indoor Environments,” International Journal of Robotic Research, Vol. 31, No. 5, 2012, pp. 647-663. doi:10.1177/0278364911434148
N. Burrus, M. Abderrahim, J. G. Bueno and L. Moreno, “Object Reconstruction and Recognition Leveraging an RGB-D Camera,” Proceedings of the 12th IAPR Conference on Machine Vision Applications, Nara, 13-15 June 2011.
S. Izadi, D. Kim, O. Hilliges, D. Molyneaux, R. Newcombe, P. Kohli, J. Shotton, S. Hodges, D. Freeman, A. Davison and A. Fitzgibbon, “KinectFusion: Real-time 3D Reconstruction and Interaction Using a Moving Depth Camera,” 24th Annual ACM Symposium on User Interface Software and Technology, Santa Barbara, 16-19 October 2011.