Abstract

Tracking a target in infrared (IR) sequences is a challenging task because of low resolution, low signal-to-noise ratios, occlusion, and poor target visibility. For many civil and military applications, the real-time requirement is always a key factor for tracking algorithms to be used. This undoubtedly makes tracking in IR sequences more difficult. This paper presents a real-time IR target tracking under complex conditions based on 1 minimization and compressive features. First, we adopt a sparse measurement matrix to project the high-dimensional Harr-like features to low-dimensional features that are applied to the appearance modeling. This appearance model allows significant reduction in the computational cost of the target-tracking phase. Then, the appearance model is introduced into the framework of the popular 1 tracker. Each IR target candidate is represented by the appearance template based on the structure of sparse representation. Finally, the candidate that has the minimum reconstruction error is selected as the tracking result. The proposed tracking method can combine the real-time advantages of the compressive tracking and the robustness of the 1 tracker. Experimental results on challenging IR image sequences including both aerial targets and ground targets show that the proposed algorithm has better robustness and real-time performance in comparison with two state-of-the-art tracking algorithms.

© 2014 Optical Society of America

Full Article  |  PDF Article
OSA Recommended Articles
Object tracking based on incremental Bi-2DPCA learning with sparse structure

Bendu Bai, Ying Li, Jiulun Fan, Chris Price, and Qiang Shen
Appl. Opt. 54(10) 2897-2907 (2015)

Robust object tracking based on local discriminative sparse representation

Xin Wang, Siqiu Shen, Chen Ning, Yuzhen Zhang, and Guofang Lv
J. Opt. Soc. Am. A 34(4) 533-544 (2017)

References

You do not have subscription access to this journal. Citation lists with outbound citation links are available to subscribers only. You may subscribe either as an OSA member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access OSA Member Subscription

Cited By

You do not have subscription access to this journal. Cited by links are available to subscribers only. You may subscribe either as an OSA member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access OSA Member Subscription

Figures (7)

You do not have subscription access to this journal. Figure files are available to subscribers only. You may subscribe either as an OSA member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access OSA Member Subscription

Tables (4)

You do not have subscription access to this journal. Article tables are available to subscribers only. You may subscribe either as an OSA member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access OSA Member Subscription

Equations (15)

You do not have subscription access to this journal. Equations are available to subscribers only. You may subscribe either as an OSA member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access OSA Member Subscription

Metrics

You do not have subscription access to this journal. Article level metrics are available to subscribers only. You may subscribe either as an OSA member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access OSA Member Subscription