TY - GEN
T1 - Design and Implementation of Scale Adaptive Kernel Correlation Filtering Algorithm Based on Hls
AU - Liu, Xinyu
AU - Ma, Zhifeng
AU - Xie, Min
AU - Zhang, Jiahe
AU - Feng, Tingyan
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021/8/17
Y1 - 2021/8/17
N2 - Moving target tracking is one of the important research subjects in the current field of computer vision, in which the correlation filter algorithms become a hotspot in theory research and application with its excellent comprehensive performance. However, the tracking frame of Kernel Correlation Filter (KCF) algorithms is fixed, and the change of target size will cause tracking drift or even target missing. This design improves it by integrating a scale filter from DSST (Discriminative Scale Space Tracking) algorithm so that it has a better Tracking effect under complex conditions such as target size change, occlusion, deformation and illumination change. At the same time, in order to balance the accuracy and real-Time performance of the algorithm, the scale adaptive kernel correlation filtering algorithm is modified in this design, and an optimized design and implementation method based on high-level synthesis (HLS) is proposed to make it more suitable for FPGA.
AB - Moving target tracking is one of the important research subjects in the current field of computer vision, in which the correlation filter algorithms become a hotspot in theory research and application with its excellent comprehensive performance. However, the tracking frame of Kernel Correlation Filter (KCF) algorithms is fixed, and the change of target size will cause tracking drift or even target missing. This design improves it by integrating a scale filter from DSST (Discriminative Scale Space Tracking) algorithm so that it has a better Tracking effect under complex conditions such as target size change, occlusion, deformation and illumination change. At the same time, in order to balance the accuracy and real-Time performance of the algorithm, the scale adaptive kernel correlation filtering algorithm is modified in this design, and an optimized design and implementation method based on high-level synthesis (HLS) is proposed to make it more suitable for FPGA.
KW - FPGA
KW - Kernel Correlation Filter
KW - scale estimation
KW - visual tracking
UR - https://www.scopus.com/pages/publications/85118429780
U2 - 10.1109/ICSPCC52875.2021.9564815
DO - 10.1109/ICSPCC52875.2021.9564815
M3 - Conference contribution
AN - SCOPUS:85118429780
T3 - Proceedings of 2021 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2021
BT - Proceedings of 2021 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2021
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2021 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2021
Y2 - 17 August 2021 through 19 August 2021
ER -