On Optimal Multi-Sensor Network Configuration for 3D Registration
Multi-sensor networks provide complementary information for various taskslike object detection, movement analysis and tracking. One of the important ingredientsfor efficient multi-sensor network actualization is the optimal configuration of sensors.In this work, we consider the problem of optimal co...
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| Format: | Article |
| Language: | English |
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MDPI AG
2015-11-01
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| Series: | Journal of Sensor and Actuator Networks |
| Subjects: | |
| Online Access: | http://www.mdpi.com/2224-2708/4/4/293 |
| _version_ | 1818619952222961664 |
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| author | Hadi Aliakbarpour V. B. Surya Prasath Jorge Dias |
| author_facet | Hadi Aliakbarpour V. B. Surya Prasath Jorge Dias |
| author_sort | Hadi Aliakbarpour |
| collection | DOAJ |
| description | Multi-sensor networks provide complementary information for various taskslike object detection, movement analysis and tracking. One of the important ingredientsfor efficient multi-sensor network actualization is the optimal configuration of sensors.In this work, we consider the problem of optimal configuration of a network of coupledcamera-inertial sensors for 3D data registration and reconstruction to determine humanmovement analysis. For this purpose, we utilize a genetic algorithm (GA) based optimizationwhich involves geometric visibility constraints. Our approach obtains optimal configurationmaximizing visibility in smart sensor networks, and we provide a systematic study usingedge visibility criteria, a GA for optimal placement, and extension from 2D to 3D.Experimental results on both simulated data and real camera-inertial fused data indicate weobtain promising results. The method is scalable and can also be applied to other smartnetwork of sensors. We provide an application in distributed coupled video-inertial sensorbased 3D reconstruction for human movement analysis in real time. |
| first_indexed | 2024-12-16T17:45:39Z |
| format | Article |
| id | doaj.art-bfb99dbaa486425da048bf2eb5ef9af4 |
| institution | Directory Open Access Journal |
| issn | 2224-2708 |
| language | English |
| last_indexed | 2024-12-16T17:45:39Z |
| publishDate | 2015-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Journal of Sensor and Actuator Networks |
| spelling | doaj.art-bfb99dbaa486425da048bf2eb5ef9af42022-12-21T22:22:29ZengMDPI AGJournal of Sensor and Actuator Networks2224-27082015-11-014429331410.3390/jsan4040293jsan4040293On Optimal Multi-Sensor Network Configuration for 3D RegistrationHadi Aliakbarpour0V. B. Surya Prasath1Jorge Dias2Computational Imaging and Visualization Analysis (CIVA) Lab, Department of Computer Science, University of Missouri-Columbia, Columbia 65211, MO, USAComputational Imaging and Visualization Analysis (CIVA) Lab, Department of Computer Science, University of Missouri-Columbia, Columbia 65211, MO, USAInstitute of Systems and Robotics, University of Coimbra, Faculty of Science and Technology, Coimbra 3000-315, PortugalMulti-sensor networks provide complementary information for various taskslike object detection, movement analysis and tracking. One of the important ingredientsfor efficient multi-sensor network actualization is the optimal configuration of sensors.In this work, we consider the problem of optimal configuration of a network of coupledcamera-inertial sensors for 3D data registration and reconstruction to determine humanmovement analysis. For this purpose, we utilize a genetic algorithm (GA) based optimizationwhich involves geometric visibility constraints. Our approach obtains optimal configurationmaximizing visibility in smart sensor networks, and we provide a systematic study usingedge visibility criteria, a GA for optimal placement, and extension from 2D to 3D.Experimental results on both simulated data and real camera-inertial fused data indicate weobtain promising results. The method is scalable and can also be applied to other smartnetwork of sensors. We provide an application in distributed coupled video-inertial sensorbased 3D reconstruction for human movement analysis in real time.http://www.mdpi.com/2224-2708/4/4/293optimal configurationsensor networkgenetic algorithm3Dreconstructionregistrationhuman movements |
| spellingShingle | Hadi Aliakbarpour V. B. Surya Prasath Jorge Dias On Optimal Multi-Sensor Network Configuration for 3D Registration Journal of Sensor and Actuator Networks optimal configuration sensor network genetic algorithm 3D reconstruction registration human movements |
| title | On Optimal Multi-Sensor Network Configuration for 3D Registration |
| title_full | On Optimal Multi-Sensor Network Configuration for 3D Registration |
| title_fullStr | On Optimal Multi-Sensor Network Configuration for 3D Registration |
| title_full_unstemmed | On Optimal Multi-Sensor Network Configuration for 3D Registration |
| title_short | On Optimal Multi-Sensor Network Configuration for 3D Registration |
| title_sort | on optimal multi sensor network configuration for 3d registration |
| topic | optimal configuration sensor network genetic algorithm 3D reconstruction registration human movements |
| url | http://www.mdpi.com/2224-2708/4/4/293 |
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