TY - GEN
T1 - DCTracker
T2 - 2nd IEEE International Conference on Signal, Information and Data Processing, ICSIDP 2024
AU - Shi, Yuting
AU - Zhuang, Yin
AU - Chen, He
AU - Cai, Miaoxin
AU - Xie, Jianlin
AU - Gan, Shuyu
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - Multi-object tracking (MOT) in satellite videos is a vital technique in Earth observation, serving various purposes such as smart city management and military target reconnaissance. However, satellite videos face several challenges, including wide observation ranges, low target pixel proportions, and significant background interference such as cloud drift and lighting changes. Relying solely on appearance features from single-frame videos is insufficient for fully identifying targets; extracting target motion information across multiple frames is also necessary for assistance.This paper introduces an innovative integrated real-time architecture for multi-object tracking, named DCTracker. Specifically, to address the loss of target motion information and the issue of weak targets being easily obscured by noise, we designed a differential compensation module to enhance discrimination between targets and noise by analyzing the motion characteristics of targets across consecutive video frames. Experimental results show that DCTracker achieves advanced performance, with an accuracy score of 61.3% on the VISO dataset, demonstrating its effectiveness in handling complex tracking scenarios.
AB - Multi-object tracking (MOT) in satellite videos is a vital technique in Earth observation, serving various purposes such as smart city management and military target reconnaissance. However, satellite videos face several challenges, including wide observation ranges, low target pixel proportions, and significant background interference such as cloud drift and lighting changes. Relying solely on appearance features from single-frame videos is insufficient for fully identifying targets; extracting target motion information across multiple frames is also necessary for assistance.This paper introduces an innovative integrated real-time architecture for multi-object tracking, named DCTracker. Specifically, to address the loss of target motion information and the issue of weak targets being easily obscured by noise, we designed a differential compensation module to enhance discrimination between targets and noise by analyzing the motion characteristics of targets across consecutive video frames. Experimental results show that DCTracker achieves advanced performance, with an accuracy score of 61.3% on the VISO dataset, demonstrating its effectiveness in handling complex tracking scenarios.
KW - differential compensation(DC)
KW - joint detection and tracking(JDT)
KW - multi-object tracking(MOT)
UR - http://www.scopus.com/inward/record.url?scp=86000020273&partnerID=8YFLogxK
U2 - 10.1109/ICSIDP62679.2024.10868218
DO - 10.1109/ICSIDP62679.2024.10868218
M3 - Conference contribution
AN - SCOPUS:86000020273
T3 - IEEE International Conference on Signal, Information and Data Processing, ICSIDP 2024
BT - IEEE International Conference on Signal, Information and Data Processing, ICSIDP 2024
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 22 November 2024 through 24 November 2024
ER -