Name
Title | ||
|---|---|---|
Comparison of infrared and visible imagery for object tracking: Toward trackers with superior IR performance |
Abstract | ||
|---|---|---|
The subject of this paper is the visual object tracking in infrared (IR) videos. Our contribution is twofold. First, the performance behaviour of the state-of-the-art trackers is investigated via a comparative study using IR-visible band video conjugates, i.e., video pairs captured observing the same scene simultaneously, to identify the IR specific challenges. Second, we propose a novel ensemble based tracking method that is tuned to IR data. The proposed algorithm sequentially constructs and maintains a dynamical ensemble of simple correlators and produces tracking decisions by switching among the ensemble correlators depending on the target appearance in a computationally highly efficient manner. We empirically show that our algorithm significantly outperforms the state-of-the-art trackers in our extensive set of experiments with IR imagery. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1109/CVPRW.2015.7301290 | 2015 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) |
Keywords | Field | DocType |
visible imagery,infrared imagery,tracker superior IR performance,visual object tracking,infrared video,IR-visible band video conjugate | Correlation function (quantum field theory),Computer vision,BitTorrent tracker,Pattern recognition,Computer science,Video tracking,Artificial intelligence,Infrared | Conference |
Volume | Issue | ISSN |
2015 | 1 | 2160-7508 |
Citations | PageRank | References |
10 | 0.49 | 20 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Erhan Gundogdu | 1 | 35 | 5.37 |
| Huseyin Ozkan | 2 | 40 | 10.44 |
| Demir, H.Seckin | 3 | 10 | 1.85 |
| Hamza Ergezer | 4 | 14 | 1.75 |
| Erdem Akagunduz | 5 | 35 | 5.09 |
| S. Kubilay Pakin | 6 | 21 | 2.84 |