Extracting minimalistic corridor geometry from low-resolution images

Authors:
Yinxiao Li;Vidya N. Murali;Stanley T. Birchfield
Affiliations:
Department of Electrical and Computer Engineering, Clemson University;Department of Electrical and Computer Engineering, Clemson University;Department of Electrical and Computer Engineering, Clemson University
Venue:
ICIRA'12 Proceedings of the 5th international conference on Intelligent Robotics and Applications - Volume Part I
Year:
2012

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Abstract

We propose a minimalistic corridor representation consisting of the orientation line (center) and the wall-floor boundaries (lateral limit). The representation is extracted from low-resolution images using a novel combination of information theoretic measures and gradient cues. Our study investigates the impact of image resolution upon the accuracy of extracting such a geometry, showing that accurate centerline and wall-floor boundaries can be estimated even in texture-poor environments with images as small as 16 ×12. In a database of 7 unique corridor sequences for orientation measurements, less than 2% additional error was observed as the resolution of the image decreased by 99%. One of the advantages of working at such resolutions is that the algorithm operates at hundreds of frames per second, or equivalently requires only a small percentage of the CPU.