CONFERENCE PROCEEDINGS
Advanced Search
Home > Proceedings > Volume 10836 > Article
Paper
29 October 2018 A complementary tracking model with multiple features
Peng Gao, Yipeng Ma, Chao Li, Ke Song, Fei Wang, Liyi Xiao
Author Affiliations +
Proceedings Volume 10836, 2018 International Conference on Image and Video Processing, and Artificial Intelligence; 1083618 (2018) https://doi.org/10.1117/12.2500635
Event: 2018 International Conference on Image, Video Processing and Artificial Intelligence, 2018, Shanghai, China
Abstract
Discriminative Correlation Filters based tracking algorithms exploiting conventional handcrafted features have achieved impressive results both in terms of accuracy and robustness. In this paper, to achieve an efficient tracking performance, we propose a novel visual tracking algorithm based on a complementary ensemble model with multiple features. Additionally, to improve tracking results and prevent targets drift, we introduce an effective fusion method by exploiting relative entropy to coalesce all basic response maps and get an optimal response. Furthermore, we suggest a simple but efficient update strategy to boost tracking performance. Comprehensive evaluations are conducted on two tracking benchmarks demonstrate and the experimental results demonstrate that our method is competitive with numerous state-of-the-art trackers. Our tracker achieves impressive performance with faster speed on these benchmarks.
© (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Citation Download Citation
Peng Gao, Yipeng Ma, Chao Li, Ke Song, Fei Wang, and Liyi Xiao "A complementary tracking model with multiple features", Proc. SPIE 10836, 2018 International Conference on Image and Video Processing, and Artificial Intelligence, 1083618 (29 October 2018); https://doi.org/10.1117/12.2500635
ACCESS THE FULL ARTICLE
ORGANIZATIONAL
Sign in with credentials provided by your organization.
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
 5 PAGES
DOWNLOAD PAPER SAVE TO MY LIBRARY
GET CITATION
Lens.org Logo
CITATIONS
Cited by 5 scholarly publications.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Detection and tracking algorithms
Digital image correlation and tracking
Information fusion
RELATED CONTENT
Subscribe to Digital Library
Receive Erratum Email Alert
Back to Top