Robotic Camera Array Motion Planning for Multiple Human Face Tracking Based on Reinforcement Learning

Pengyu Wang1; Rui Ma2; Zijiang Yang1; Qi Hao3

2024

10.1109/JSEN.2024.3415954

IEEE Sensors Journal   影响因子和分区

2379-9153

Active camera networks have been widely applied for mobile target sensing. However, traditional model/rule-based methods run into bottlenecks when dealing with complex dynamic scenarios due to their lack of long-term planning abilities. This paper presents a mobile camera array consisting of multiple robotic cameras which actively arrange their locations and poses to increase the human face tracking efficiency by leveraging reinforcement learning (RL) techniques. The novelty of the proposed system is threefold: 1) developing a distributed RL network based on the Soft Actor-Critic model to increase the learning efficiency and to capture targets’ long-term behaviors; 2) developing a reward function for the RL networks to facilitate the cooperation among multiple cameras; 3) developing the self-attention modules in the distributed RL networks to enhance the multi-agent global state estimation from local cameras. The developed system is validated through human face detection and recognition applications. The simulation and real-world experiment results demonstrate the efficiency and superior performance of the proposed methods.

EI

第一

ENGINEERING

1.Department of Computer Science and Engineering, Southern University of Science and Technology, Shenzhen, China
2.School of Computer Science and Engineering / School of Software, Guangxi Normal University, Guilin, China
3.Research Institute of Trustworthy Autonomous Systems and the Department of Computer Science and Engineering, Southern University of Science and Technology, Shenzhen, China

Pengyu Wang,Rui Ma,Zijiang Yang,et al. Robotic Camera Array Motion Planning for Multiple Human Face Tracking Based on Reinforcement Learning[J]. IEEE Sensors Journal,2024,PP(99).

Pengyu Wang,Rui Ma,Zijiang Yang,&Qi Hao.(2024).Robotic Camera Array Motion Planning for Multiple Human Face Tracking Based on Reinforcement Learning.IEEE Sensors Journal,PP(99).

Pengyu Wang,et al."Robotic Camera Array Motion Planning for Multiple Human Face Tracking Based on Reinforcement Learning".IEEE Sensors Journal PP.99(2024).