4 February 2013 Loop closure detection using local Zernike moment patterns
Author Affiliations +
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, Evangelos Sariyanidi, Onur Sencan, Onur Sencan, Hakan Temeltas, Hakan Temeltas, } "Loop closure detection using local Zernike moment patterns", Proc. SPIE 8662, Intelligent Robots and Computer Vision XXX: Algorithms and Techniques, 866207 (4 February 2013); doi: 10.1117/12.2008473; https://doi.org/10.1117/12.2008473


A RANSAC-ST method for image matching
Proceedings of SPIE (March 01 2016)
Multipole methods for visual reconstruction
Proceedings of SPIE (June 22 1993)
Edge Linking by Ellipsoidal Clustering
Proceedings of SPIE (February 28 1990)
Image categorization based on multi-scale vocabulary
Proceedings of SPIE (November 14 2007)

Back to Top