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22 September 2015 A fusion algorithm for building three-dimensional maps
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Abstract
Recently various algorithms for building of three-dimensional maps of indoor environments have been proposed. In this work we use a Kinect camera that captures RGB images along with depth information for building three-dimensional dense maps of indoor environments. Commonly mapping systems consist of three components; that is, first, spatial alignment of consecutive data frames; second, detection of loop-closures, and finally, globally consistent alignment of the data sequence. It is known that three-dimensional point clouds are well suited for frame-to-frame alignment and for three-dimensional dense reconstruction without the use of valuable visual RGB information. A new fusion algorithm combining visual features and depth information for loop-closure detection followed by pose optimization to build global consistent maps is proposed. The performance of the proposed system in real indoor environments is presented and discussed.
© (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
A. Vokhmintsev, A. Makovetskii, V. Kober, I. Sochenkov, and V. Kuznetsov "A fusion algorithm for building three-dimensional maps", Proc. SPIE 9599, Applications of Digital Image Processing XXXVIII, 959929 (22 September 2015); https://doi.org/10.1117/12.2187929
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