On Optimal Multi-Sensor Network Configuration for 3D Registration
AbstractMulti-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. View Full-Text
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Aliakbarpour, H.; Prasath, V.B.S.; Dias, J. On Optimal Multi-Sensor Network Configuration for 3D Registration. J. Sens. Actuator Netw. 2015, 4, 293-314.
Aliakbarpour H, Prasath VBS, Dias J. On Optimal Multi-Sensor Network Configuration for 3D Registration. Journal of Sensor and Actuator Networks. 2015; 4(4):293-314.Chicago/Turabian Style
Aliakbarpour, Hadi; Prasath, V. B.S.; Dias, Jorge. 2015. "On Optimal Multi-Sensor Network Configuration for 3D Registration." J. Sens. Actuator Netw. 4, no. 4: 293-314.