This paper introduces a novel image description technique that aims at appearance based loop closure detection
for mobile robotics applications. This technique relies on the local evaluation of the Zernike Moments. Binary
patterns, which are referred to as Local Zernike Moment (LZM) patterns, are extracted from images, and these
binary patterns are coded using histograms. Each image is represented with a set of histograms, and loop closure
is achieved by simply comparing the most recent image with the images in the past trajectory. The technique
has been tested on the New College dataset, and as far as we know, it outperforms the other methods in terms
of computation efficiency and loop closure precision.
© (2013) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Evangelos Sariyanidi ; Onur Sencan and Hakan Temeltas
Loop closure detection using local Zernike moment patterns
", Proc. SPIE 8662, Intelligent Robots and Computer Vision XXX: Algorithms and Techniques, 866207 (February 4, 2013); doi:10.1117/12.2008473; http://dx.doi.org/10.1117/12.2008473