A robust, real-time ground change detector for a "smart" walker

Weiss, Viviana (Computer Science Department, University of Geneva, Geneva, Switzerland) ; Cloix, Séverine (Vision Embedded Systems, CSEM SA, Neuchâtel, Switzerland) ; Bologna, Guido (Computer Science Department, University of Geneva, Geneva, Switzerland) ; Hasler, David (Vision Embedded Systems, CSEM SA, Neuchâtel, Switzerland) ; Pun, Thierry (Computer Science Department, University of Geneva, Geneva, Switzerland)

Nowadays, there are many different types of mobility aids for elderly people. Nevertheless, these devices may lead to accidents, depending on the terrain where they are being used. In this paper, we present a robust ground change detector that will warn the user of potentially risky situations. Specifically, we propose a robust classification algorithm to detect ground changes based on colour histograms and texture descriptors. In our design, we compare the current frame and the average of the k previous frames using different colour systems and Local Edge Patterns. To assess the performance of our algorithm, we evaluated different Artificial Neural Networks architectures. The best results were obtained by representing in the input neurons measures related to Histogram Intersections, Kolmogorov-Smirnov distance, Cumulative Integrals and Earth mover's distance. Under real environmental conditions our results indicated that our proposed detector can accurately distinguish the grounds changes in real-time.


Note: BOLOGNA, Guido est un chercheur à la HES-SO, HEPIA, depuis 2011.


Keywords:
Conference Type:
full paper
Faculty:
Ingénierie et Architecture
School:
HEPIA - Genève
Institute:
inIT - Institut d'Ingénierie Informatique et des Télécommunications
Publisher:
Lisbon, Portugal, 5-8 January 2014
Date:
2014-01
Lisbon, Portugal
5-8 January 2014
Pagination:
7 p.
Published in:
Proceedings of 2014 International Conference on Computer Vision Theory and Applications (VISAPP), 8-8 January 2014, Lisbon, Portugal
ISBN:
978-9-8975-8133-5
Appears in Collection:

Note: The status of this file is: restricted


 Record created 2020-07-10, last modified 2020-07-17

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