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Authors: Hossam Fraihat ; Kurosh Madani and Christophe Sabourin

Affiliation: University Paris-Est Creteil and Senart-FB Institute of Technology, France

ISBN: 978-989-758-157-1

Keyword(s): Visual distance evaluation, Soft-Computing, Kinect, Visual information processing, Machine learning, ANFIS, MLP, SVR, Bilinear interpolation.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Artificial Intelligence and Decision Support Systems ; Biomedical Engineering ; Biomedical Signal Processing ; Computational Intelligence ; Enterprise Information Systems ; Health Engineering and Technology Applications ; Human-Computer Interaction ; Image Processing and Artificial Vision Applications ; Methodologies and Methods ; Neural Network Software and Applications ; Neural Networks ; Neurocomputing ; Neurotechnology, Electronics and Informatics ; Pattern Recognition ; Physiological Computing Systems ; Sensor Networks ; Signal Processing ; Soft Computing ; Theory and Methods

Abstract: This paper deals with visual evaluation of object distances using Soft-Computing based approaches and pseudo-3D standard low-cost sensor, namely the Kinect. The investigated technique points toward robots’ vision and visual metrology of the robot’s surrounding environment. The objective is providing the robot the ability of evaluating distances between objects in its surrounding environment. In fact, although presenting appealing advantages, the Kinect has not been designed for metrological aims. The investigated approach offers the possibility to use this low-cost pseudo-3D sensor for distance evaluation avoiding 3D feature extraction and thus exploiting the simplicity of only 2D image’ processing. Experimental results show the viability of the proposed approach and provide comparison between different machine learning techniques as Adaptive-network-based fuzzy inference (ANFIS), Multi-layer Perceptron (MLP), Support vector regression (SVR), Bilinear interpolation.

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Paper citation in several formats:
Fraihat, H.; Madani, K. and Sabourin, C. (2015). Learning-based Distance Evaluation in Robot Vision - A Comparison of ANFIS, MLP, SVR and Bilinear Interpolation Models.In Proceedings of the 7th International Joint Conference on Computational Intelligence - Volume 3: NCTA, (ECTA 2015) ISBN 978-989-758-157-1, pages 168-173. DOI: 10.5220/0005636301680173

@conference{ncta15,
author={Hossam Fraihat. and Kurosh Madani. and Christophe Sabourin.},
title={Learning-based Distance Evaluation in Robot Vision - A Comparison of ANFIS, MLP, SVR and Bilinear Interpolation Models},
booktitle={Proceedings of the 7th International Joint Conference on Computational Intelligence - Volume 3: NCTA, (ECTA 2015)},
year={2015},
pages={168-173},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005636301680173},
isbn={978-989-758-157-1},
}

TY - CONF

JO - Proceedings of the 7th International Joint Conference on Computational Intelligence - Volume 3: NCTA, (ECTA 2015)
TI - Learning-based Distance Evaluation in Robot Vision - A Comparison of ANFIS, MLP, SVR and Bilinear Interpolation Models
SN - 978-989-758-157-1
AU - Fraihat, H.
AU - Madani, K.
AU - Sabourin, C.
PY - 2015
SP - 168
EP - 173
DO - 10.5220/0005636301680173

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