Siamese network tracker with channel attention mechanism

Sen Zhang; Yun Gao

doi:10.1117/12.2623577

16 February 2022 Siamese network tracker with channel attention mechanism

Sen Zhang, Yun Gao

Proceedings Volume 12083, Thirteenth International Conference on Graphics and Image Processing (ICGIP 2021); 120830W (2022) https://doi.org/10.1117/12.2623577
Event: Thirteenth International Conference on Graphics and Image Processing (ICGIP 2021), 2021, Kunming, China

Abstract

Recently, object trackers based on Siamese deep network have achieved great progress and attract much attention. It can be helpful to improve the performance of a tracker to mining more effective information from feature maps. In this paper, we propose a Siamese network tracker with channel attention mechanism based on the SiamCAR tracker. Firstly, in each residual unit of the ResNet backbone network, each channel feature of the feature map has different importance for discriminating an object. Channel attention mechanism can be used to calculate the importance of each channel feature. Secondly, deep features and lower-level features play different roles for tracking too, and attention mechanisms can be used to fuse the features of each residual stage. On the benchmark datasets, OTB50 and OTB100, the experiments show that our proposed tracker achieves better tracking performance in AUC and Precision and achieves the real-time speed of 46 FPS.

Citation Download Citation

Sen Zhang and Yun Gao "Siamese network tracker with channel attention mechanism", Proc. SPIE 12083, Thirteenth International Conference on Graphics and Image Processing (ICGIP 2021), 120830W (16 February 2022); https://doi.org/10.1117/12.2623577

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
9 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Feature extraction

Autoregressive models

Video

Detection and tracking algorithms

Image filtering

Convolution

Video acceleration

Keywords/Phrases

Search In:

Publication Years