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Sensors 2011, 11(7), 7262-7284; doi:10.3390/s110707262

Visual Odometry Based on Structural Matching of Local Invariant Features Using Stereo Camera Sensor

1
Departamento de Tecnología de los Computadores y las Comunicaciones, University of Extremadura, Escuela Politécnica, Avda. Universidad s/n, 10071 Cáceres, Spain
2
CITIC Centro Andaluz de Innovación y Tecnologías de la Información y las Comunicaciones, Parque Tecnológico de Andalucía, 29590 Málaga, Spain
3
Departamento de Tecnología Electrónica, University of Málaga, E.T.S.I. Telecomunicación, Campus Teatinos 29071 Málaga, Spain
*
Author to whom correspondence should be addressed.
Received: 29 May 2011 / Revised: 12 July 2011 / Accepted: 12 July 2011 / Published: 18 July 2011
(This article belongs to the Section Physical Sensors)
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Abstract

This paper describes a novel sensor system to estimate the motion of a stereo camera. Local invariant image features are matched between pairs of frames and linked into image trajectories at video rate, providing the so-called visual odometry, i.e., motion estimates from visual input alone. Our proposal conducts two matching sessions: the first one between sets of features associated to the images of the stereo pairs and the second one between sets of features associated to consecutive frames. With respect to previously proposed approaches, the main novelty of this proposal is that both matching algorithms are conducted by means of a fast matching algorithm which combines absolute and relative feature constraints. Finding the largest-valued set of mutually consistent matches is equivalent to finding the maximum-weighted clique on a graph. The stereo matching allows to represent the scene view as a graph which emerge from the features of the accepted clique. On the other hand, the frame-to-frame matching defines a graph whose vertices are features in 3D space. The efficiency of the approach is increased by minimizing the geometric and algebraic errors to estimate the final displacement of the stereo camera between consecutive acquired frames. The proposed approach has been tested for mobile robotics navigation purposes in real environments and using different features. Experimental results demonstrate the performance of the proposal, which could be applied in both industrial and service robot fields. View Full-Text
Keywords: visual odometry sensor; stereo vision sensor; robotic; combined constraint matching algorithm; maximum-weighted clique visual odometry sensor; stereo vision sensor; robotic; combined constraint matching algorithm; maximum-weighted clique
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This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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MDPI and ACS Style

Núñez, P.; Vázquez-Martín, R.; Bandera, A. Visual Odometry Based on Structural Matching of Local Invariant Features Using Stereo Camera Sensor. Sensors 2011, 11, 7262-7284.

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