Development Of Mobile Camera Arrays For Object Detection Applications

The smart camera networks(SCNs)have been widely used in various scenarios such as public safety and indoor anomaly detection.In recent years,combining reconfigurable cameras and on-board processing units with wireless communication modules to build surveillance systems has become a mainstream technology.Developments of advanced topologies,intelligent resource allocation and parameter reconfiguration schemes for SCNs have attracted many research attentions.The related major technical challenges include:(1)how to increase system scalability and stability;(2)how to make use of multi-view information and efficiently perform multi-camera parameter reconfiguration to carry out expected tasks,and(3)how to verify the effectiveness of system deployments and proposed algorithms.This work proposes a novel integrated framework for the development of smart mobile camera array systems.Advantages of this work include three aspects:(1)a distributed topology is used to achieve the system scalability,and each individual unit's control accuracy and stability under high motility are improved by applying classic control methods to the feedback data from IMU and odometry;(2)heuristic search methods are developed to achieve system motion planning for multi-view based tasks,and deep learning based image processing algorithms are implemented to help improve the multi-view detection and scene analysis performances;(3)compared with existing works,algorithm migrations between the Unreal Engine based 3D simulation environment and the hardware platform are flexible,so results of experiments and simulations can be integrated,which is conducive to the safe and efficient studies of deploying mobile camera arrays and optimizing system performance under different constraints.Corresponding hardware and 3D simulation platforms are built and numerous experiments are carried out.Results show that in terms of target detection tasks,proposed heuristic reconfiguration methods can achieve good results in a shorter time compared with other existing methods;and the whole system works stably to meet various performance requirements,laying a solid foundation for extending advanced applications.