- Tytuł:
- Single target tracking algorithm for lightweight Siamese networks based on global attention
- Autorzy:
-
Wang, Zhentao
He, Xiaowei
Cheng, Rao - Powiązania:
- https://bibliotekanauki.pl/articles/2173664.pdf
- Data publikacji:
- 2022
- Wydawca:
- Polska Akademia Nauk. Czytelnia Czasopism PAN
- Tematy:
-
target tracking
Siamese network
semantic information
training strategy
feature fusion
deep learning
śledzenie celu
sieć syjamska
informacja semantyczna
strategia szkolenia
fuzja funkcji
głęboka nauka - Opis:
- Object tracking based on Siamese networks has achieved great success in recent years, but increasingly advanced trackers are also becoming cumbersome, which will severely limit deployment on resource-constrained devices. To solve the above problems, we designed a network with the same or higher tracking performance as other lightweight models based on the SiamFC lightweight tracking model. At the same time, for the problems that the SiamFC tracking network is poor in processing similar semantic information, deformation, illumination change, and scale change, we propose a global attention module and different scale training and testing strategies to solve them. To verify the effectiveness of the proposed algorithm, this paper has done comparative experiments on the ILSVRC, OTB100, VOT2018 datasets. The experimental results show that the method proposed in this paper can significantly improve the performance of the benchmark algorithm.
- Źródło:
-
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2022, 70, 3; art. no. e139961
0239-7528 - Pojawia się w:
- Bulletin of the Polish Academy of Sciences. Technical Sciences
- Dostawca treści:
- Biblioteka Nauki
Artykuł