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RICHTER, M. PETYOVSKÝ, P. MIKŠÍK, O.
Original Title
Adapting Polynomial Mahalanobis Distance for Self-Supervised Learning in an Outdoor Environment
Type
conference paper
Language
English
Original Abstract
This paper addresses the problem of autonomous navigation of UGV in an unstructured environment. Generally, state-of-the-art approaches use color based segmentation of road/non-road regions in particular. There arises an important question, how is the distance between an input pixel and a color model measured. Many algorithms employ Mahalanobis distance, since Mahalanobis distance better follows the data distribution, however it is assumed, that the data points have a normal distribution. Recently proposed Polynomial Mahalanobis Distance (PMD) represents more discriminative metric, which provides superior results in an unstructured terrain, especially, if the road is barely visible even for humans. In this paper, we discuss properties of the Polynomial Mahalanobis Distance, and propose a novel framework - A Three Stage Algorithm (TSA), which deals with both, picking of suitable data points from the training area as well as self-supervised learning algorithm for long-term road representation.
Keywords
Polynomial Mahalanobis Distance, A Three Stage Algorithm, Self-supervised Learning, Robotics
Authors
RICHTER, M.; PETYOVSKÝ, P.; MIKŠÍK, O.
RIV year
2012
Released
3. 1. 2012
Publisher
The Institute of Electrical and Electronics Engineers, Inc.
ISBN
978-1-4577-2134-2
Book
Proceedings, The 10th International Conference on Machine Learning and Applications, ICMLA 2011, Volume 1: Main Conference (ISBN 978-1-4577-2134-2 , 978-0-7695-4607-0)
Pages from
448
Pages to
453
Pages count
6
BibTex
@inproceedings{BUT89729, author="Miloslav {Richter} and Petr {Petyovský} and Ondřej {Mikšík}", title="Adapting Polynomial Mahalanobis Distance for Self-Supervised Learning in an Outdoor Environment", booktitle="Proceedings, The 10th International Conference on Machine Learning and Applications, ICMLA 2011, Volume 1: Main Conference (ISBN 978-1-4577-2134-2 , 978-0-7695-4607-0)", year="2012", pages="448--453", publisher="The Institute of Electrical and Electronics Engineers, Inc.", isbn="978-1-4577-2134-2" }