1 April 1991 Robust self-calibration and evidential reasoning for building environment maps
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Proceedings Volume 1383, Sensor Fusion III: 3D Perception and Recognition; (1991) https://doi.org/10.1117/12.25270
Event: Advances in Intelligent Robotics Systems, 1990, Boston, MA, United States
Abstract
We address the problem of building a map of the environment utilizing sensory depth information obtained from multiple viewpoints. The desired representation of the environment is in the form of a finite-resolution three-dimensional grid of voxels. Each voxel within the grid is assigned a binary value corresponding to its occupancy state. We present an approach for multi-sensory depth information assimilation based on Dempster-Shafer theory for evidential reasoning. This approach provides a mechanism to explicitly model ignorance which is desirable when dealing with an unknown environment. A fundamental requirement for such an approach to be used is accurate knowledge of the camera motion between two viewpoints. We present a robust least median of squares (LMS) based algorithm to recover this motion which provides a self-calibration mechanism. We present results obtained from this approach on a laboratory stereo sequence.
© (1991) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Arun P. Tirumalai, Arun P. Tirumalai, Brian G. Schunck, Brian G. Schunck, Ramesh C. Jain, Ramesh C. Jain, } "Robust self-calibration and evidential reasoning for building environment maps", Proc. SPIE 1383, Sensor Fusion III: 3D Perception and Recognition, (1 April 1991); doi: 10.1117/12.25270; https://doi.org/10.1117/12.25270
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