TY - GEN
T1 - Infrared target detection and tracking based on brain-inspired model and DNNs
AU - Song, Yong
AU - Zhao, Yufei
AU - Yang, Xin
AU - Wu, Yao
AU - Teng, Feifei
AU - Hao, Qun
N1 - Publisher Copyright:
© COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.
PY - 2020
Y1 - 2020
N2 - Infrared target detection and tracking technology has been widely used in the fields of transportation, medical, safety and military affairs, etc. However, there stills exists some challenges in infrared target detection and tracking, such as dim small target, complex background, target occlusion and appearance changes, etc. On the other hand, as the most effective bio-intelligence system, Human Visual System (HVS) has significant advantages in image processing. In this paper, several brain-inspired models (including lateral inhibition, receptive field, synchronous burst, visual attention, and cognitive memory) and Deep Neural Networks (DNNs) have been studied. Furthermore, the relevant mathematical models are established, the corresponding algorithms are proposed, and the comparison experiments are conducted. In summary, applying the brain-inspired models and DNNs to the infrared target detection and tracking is beneficial to achieve the accurate infrared target detection and robust tracking under complex conditions.
AB - Infrared target detection and tracking technology has been widely used in the fields of transportation, medical, safety and military affairs, etc. However, there stills exists some challenges in infrared target detection and tracking, such as dim small target, complex background, target occlusion and appearance changes, etc. On the other hand, as the most effective bio-intelligence system, Human Visual System (HVS) has significant advantages in image processing. In this paper, several brain-inspired models (including lateral inhibition, receptive field, synchronous burst, visual attention, and cognitive memory) and Deep Neural Networks (DNNs) have been studied. Furthermore, the relevant mathematical models are established, the corresponding algorithms are proposed, and the comparison experiments are conducted. In summary, applying the brain-inspired models and DNNs to the infrared target detection and tracking is beneficial to achieve the accurate infrared target detection and robust tracking under complex conditions.
KW - Deep Neural Networks
KW - Human Visual System
KW - brain-inspired models
UR - http://www.scopus.com/inward/record.url?scp=85082727432&partnerID=8YFLogxK
U2 - 10.1117/12.2543847
DO - 10.1117/12.2543847
M3 - Conference contribution
AN - SCOPUS:85082727432
T3 - Proceedings of SPIE - The International Society for Optical Engineering
BT - 2019 International Conference on Optical Instruments and Technology
A2 - Zhang, Cunlin
A2 - Zhang, Xi-Cheng
A2 - Huang, Zhiming
PB - SPIE
T2 - 2019 International Conference on Optical Instruments and Technology: IRMMW-THz Technologies and Applications
Y2 - 26 October 2019 through 28 October 2019
ER -