TY - GEN
T1 - Moving target detection algorithm combined background compensation with optical flow
AU - Liu, Lifei
AU - Zhao, Long
N1 - Publisher Copyright:
© 2014 IEEE.
PY - 2015/1/12
Y1 - 2015/1/12
N2 - In order to solve the problem of moving target detection caused by the ineffective calculation of the optical flow and the insufficient background compensation, an algorithm combined dynamic background compensation and optical flow is proposed. SURF (Speeded Up Robust Features) algorithm is adopted to extract the matching points and the iterative threshold segmentation algorithm is used to filter the outside point to improve matching accuracy. The motion estimation parameters are estimated by using the least-square theory. On the basis of accurate background compensation, the LK (Lucas-Kanade) optical flow algorithm is used to detect moving targets, which effectively reduces invalid background light flow calculation as well as the effect to target recognition and improves the motion target detection accuracy. Finally, VC++ and OpenCV software platform is used to design the system environment and realize the detection of moving objects in the scene of moving background. The simulation experiment results verified the feasibility of the proposed algorithm.
AB - In order to solve the problem of moving target detection caused by the ineffective calculation of the optical flow and the insufficient background compensation, an algorithm combined dynamic background compensation and optical flow is proposed. SURF (Speeded Up Robust Features) algorithm is adopted to extract the matching points and the iterative threshold segmentation algorithm is used to filter the outside point to improve matching accuracy. The motion estimation parameters are estimated by using the least-square theory. On the basis of accurate background compensation, the LK (Lucas-Kanade) optical flow algorithm is used to detect moving targets, which effectively reduces invalid background light flow calculation as well as the effect to target recognition and improves the motion target detection accuracy. Finally, VC++ and OpenCV software platform is used to design the system environment and realize the detection of moving objects in the scene of moving background. The simulation experiment results verified the feasibility of the proposed algorithm.
UR - https://www.scopus.com/pages/publications/84922513340
U2 - 10.1109/CGNCC.2014.7007370
DO - 10.1109/CGNCC.2014.7007370
M3 - 会议稿件
AN - SCOPUS:84922513340
T3 - 2014 IEEE Chinese Guidance, Navigation and Control Conference, CGNCC 2014
SP - 1186
EP - 1190
BT - 2014 IEEE Chinese Guidance, Navigation and Control Conference, CGNCC 2014
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 6th IEEE Chinese Guidance, Navigation and Control Conference, CGNCC 2014
Y2 - 8 August 2014 through 10 August 2014
ER -