3D Distance Measurement from a Camera to a Mobile Vehicle, Using Monocular Vision
Estimation of distance from objects in real-world scenes is an important topic in several applications such as navigation of autonomous robots, simultaneous localization and mapping (SLAM), and augmented reality (AR). Even though there is a technology for this purpose, in some cases, this technology...
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Online Access: | http://dx.doi.org/10.1155/2021/5526931 |
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doaj-8350e03f45774b6c9699ac1bb49414e52021-04-26T00:04:27ZengHindawi LimitedJournal of Sensors1687-72682021-01-01202110.1155/2021/55269313D Distance Measurement from a Camera to a Mobile Vehicle, Using Monocular VisionSaúl Martínez-Díaz0División de Estudios de Posgrado e InvestigaciónEstimation of distance from objects in real-world scenes is an important topic in several applications such as navigation of autonomous robots, simultaneous localization and mapping (SLAM), and augmented reality (AR). Even though there is a technology for this purpose, in some cases, this technology has some disadvantages. For example, GPS systems are susceptible to interference, especially in places surrounded by buildings, under bridges or indoors; alternatively, RGBD sensors can be used, but they are expensive, and their operational range is limited. Monocular vision is a low-cost suitable alternative that can be used indoor and outdoor. However, monocular odometry is challenging because the object location can be known up a scale factor. Moreover, when objects are moving, it is necessary to estimate the location from consecutive images accumulating error. This paper introduces a new method to compute the distance from a single image of the desired object, with known dimensions, captured with a monocular calibrated vision system. This method is less restrictive than other proposals in the state-of-the-art literature. For the detection of interest points, a Region-based Convolutional Neural Network combined with a corner detector were used. The proposed method was tested on a standard dataset and images acquired by a low-cost and low-resolution webcam, under noncontrolled conditions. The system was tested and compared with a calibrated stereo vision system. Results showed the similar performance of both systems, but the monocular system accomplished the task in less time.http://dx.doi.org/10.1155/2021/5526931 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Saúl Martínez-Díaz |
spellingShingle |
Saúl Martínez-Díaz 3D Distance Measurement from a Camera to a Mobile Vehicle, Using Monocular Vision Journal of Sensors |
author_facet |
Saúl Martínez-Díaz |
author_sort |
Saúl Martínez-Díaz |
title |
3D Distance Measurement from a Camera to a Mobile Vehicle, Using Monocular Vision |
title_short |
3D Distance Measurement from a Camera to a Mobile Vehicle, Using Monocular Vision |
title_full |
3D Distance Measurement from a Camera to a Mobile Vehicle, Using Monocular Vision |
title_fullStr |
3D Distance Measurement from a Camera to a Mobile Vehicle, Using Monocular Vision |
title_full_unstemmed |
3D Distance Measurement from a Camera to a Mobile Vehicle, Using Monocular Vision |
title_sort |
3d distance measurement from a camera to a mobile vehicle, using monocular vision |
publisher |
Hindawi Limited |
series |
Journal of Sensors |
issn |
1687-7268 |
publishDate |
2021-01-01 |
description |
Estimation of distance from objects in real-world scenes is an important topic in several applications such as navigation of autonomous robots, simultaneous localization and mapping (SLAM), and augmented reality (AR). Even though there is a technology for this purpose, in some cases, this technology has some disadvantages. For example, GPS systems are susceptible to interference, especially in places surrounded by buildings, under bridges or indoors; alternatively, RGBD sensors can be used, but they are expensive, and their operational range is limited. Monocular vision is a low-cost suitable alternative that can be used indoor and outdoor. However, monocular odometry is challenging because the object location can be known up a scale factor. Moreover, when objects are moving, it is necessary to estimate the location from consecutive images accumulating error. This paper introduces a new method to compute the distance from a single image of the desired object, with known dimensions, captured with a monocular calibrated vision system. This method is less restrictive than other proposals in the state-of-the-art literature. For the detection of interest points, a Region-based Convolutional Neural Network combined with a corner detector were used. The proposed method was tested on a standard dataset and images acquired by a low-cost and low-resolution webcam, under noncontrolled conditions. The system was tested and compared with a calibrated stereo vision system. Results showed the similar performance of both systems, but the monocular system accomplished the task in less time. |
url |
http://dx.doi.org/10.1155/2021/5526931 |
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