A New Approach for Combining Time-of-Flight and RGB Cameras Based on Depth-Dependent Planar Projective Transformations
Image registration for sensor fusion is a valuable technique to acquire 3D and colour information for a scene. Nevertheless, this process normally relies on feature-matching techniques, which is a drawback for combining sensors that are not able to deliver common features. The combination of ToF and...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2015-09-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | http://www.mdpi.com/1424-8220/15/9/24615 |
| _version_ | 1811262837817868288 |
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| author | Carlota Salinas Roemi Fernández Héctor Montes Manuel Armada |
| author_facet | Carlota Salinas Roemi Fernández Héctor Montes Manuel Armada |
| author_sort | Carlota Salinas |
| collection | DOAJ |
| description | Image registration for sensor fusion is a valuable technique to acquire 3D and colour information for a scene. Nevertheless, this process normally relies on feature-matching techniques, which is a drawback for combining sensors that are not able to deliver common features. The combination of ToF and RGB cameras is an instance that problem. Typically, the fusion of these sensors is based on the extrinsic parameter computation of the coordinate transformation between the two cameras. This leads to a loss of colour information because of the low resolution of the ToF camera, and sophisticated algorithms are required to minimize this issue. This work proposes a method for sensor registration with non-common features and that avoids the loss of colour information. The depth information is used as a virtual feature for estimating a depth-dependent homography lookup table (Hlut). The homographies are computed within sets of ground control points of 104 images. Since the distance from the control points to the ToF camera are known, the working distance of each element on the Hlut is estimated. Finally, two series of experimental tests have been carried out in order to validate the capabilities of the proposed method. |
| first_indexed | 2024-04-12T19:34:08Z |
| format | Article |
| id | doaj.art-5eaf9fcdbf0f427d9ea1d8a22900ff91 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-12T19:34:08Z |
| publishDate | 2015-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-5eaf9fcdbf0f427d9ea1d8a22900ff912022-12-22T03:19:16ZengMDPI AGSensors1424-82202015-09-01159246152464310.3390/s150924615s150924615A New Approach for Combining Time-of-Flight and RGB Cameras Based on Depth-Dependent Planar Projective TransformationsCarlota Salinas0Roemi Fernández1Héctor Montes2Manuel Armada3Centre for Automation and Robotics (CAR) CSIC-UPM, Ctra. Campo Real, Km. 0,200, La Poveda. Arganda del Rey, Madrid 28500, SpainCentre for Automation and Robotics (CAR) CSIC-UPM, Ctra. Campo Real, Km. 0,200, La Poveda. Arganda del Rey, Madrid 28500, SpainCentre for Automation and Robotics (CAR) CSIC-UPM, Ctra. Campo Real, Km. 0,200, La Poveda. Arganda del Rey, Madrid 28500, SpainCentre for Automation and Robotics (CAR) CSIC-UPM, Ctra. Campo Real, Km. 0,200, La Poveda. Arganda del Rey, Madrid 28500, SpainImage registration for sensor fusion is a valuable technique to acquire 3D and colour information for a scene. Nevertheless, this process normally relies on feature-matching techniques, which is a drawback for combining sensors that are not able to deliver common features. The combination of ToF and RGB cameras is an instance that problem. Typically, the fusion of these sensors is based on the extrinsic parameter computation of the coordinate transformation between the two cameras. This leads to a loss of colour information because of the low resolution of the ToF camera, and sophisticated algorithms are required to minimize this issue. This work proposes a method for sensor registration with non-common features and that avoids the loss of colour information. The depth information is used as a virtual feature for estimating a depth-dependent homography lookup table (Hlut). The homographies are computed within sets of ground control points of 104 images. Since the distance from the control points to the ToF camera are known, the working distance of each element on the Hlut is estimated. Finally, two series of experimental tests have been carried out in order to validate the capabilities of the proposed method.http://www.mdpi.com/1424-8220/15/9/24615high resolution RGB-D mapsdepth-dependent homography lookup tableimage registrationuncalibrated methods |
| spellingShingle | Carlota Salinas Roemi Fernández Héctor Montes Manuel Armada A New Approach for Combining Time-of-Flight and RGB Cameras Based on Depth-Dependent Planar Projective Transformations Sensors high resolution RGB-D maps depth-dependent homography lookup table image registration uncalibrated methods |
| title | A New Approach for Combining Time-of-Flight and RGB Cameras Based on Depth-Dependent Planar Projective Transformations |
| title_full | A New Approach for Combining Time-of-Flight and RGB Cameras Based on Depth-Dependent Planar Projective Transformations |
| title_fullStr | A New Approach for Combining Time-of-Flight and RGB Cameras Based on Depth-Dependent Planar Projective Transformations |
| title_full_unstemmed | A New Approach for Combining Time-of-Flight and RGB Cameras Based on Depth-Dependent Planar Projective Transformations |
| title_short | A New Approach for Combining Time-of-Flight and RGB Cameras Based on Depth-Dependent Planar Projective Transformations |
| title_sort | new approach for combining time of flight and rgb cameras based on depth dependent planar projective transformations |
| topic | high resolution RGB-D maps depth-dependent homography lookup table image registration uncalibrated methods |
| url | http://www.mdpi.com/1424-8220/15/9/24615 |
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