Paper
19 February 2018 Discussion among different methods of updating model filter in object tracking
Author Affiliations +
Proceedings Volume 10608, MIPPR 2017: Automatic Target Recognition and Navigation; 106080E (2018) https://doi.org/10.1117/12.2285038
Event: Tenth International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR2017), 2017, Xiangyang, China
Abstract
Discriminative correlation filters (DCF) have recently shown excellent performance in visual object tracking area. In this paper we summarize the methods of updating model filter from discriminative correlation filter (DCF) based tracking algorithms and analyzes similarities and differences among these methods. We deduce the relationship among updating coefficient in high dimension (kernel trick), updating filter in frequency domain and updating filter in spatial domain, and analyze the difference among these different ways. We also analyze the difference between the updating filter directly and updating filter’s numerator (object response power) with updating filter’s denominator (filter’s power). The experiments about comparing different updating methods and visualizing the template filters are used to prove our derivation.
© (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Taihang Dong and Sheng Zhong "Discussion among different methods of updating model filter in object tracking", Proc. SPIE 10608, MIPPR 2017: Automatic Target Recognition and Navigation, 106080E (19 February 2018); https://doi.org/10.1117/12.2285038
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Image filtering

Visualization

Spatial filters

Optical tracking

Detection and tracking algorithms

Video

Algorithms

Back to Top