Name
Abstract | ||
|---|---|---|
We propose an RGB-D single-object tracker, built upon the extremely fast RGB-only KCF tracker that is able to exploit depth information to handle scale changes, occlusions, and shape changes. Despite the computational demands of the extra functionalities, we still achieve real-time performance rates of 35–43 fps in MATLAB and 187 fps in our C++ implementation. Our proposed method includes fast depth-based target object segmentation that enables, (1) efficient scale change handling within the KCF core functionality in the Fourier domain, (2) the detection of occlusions by temporal analysis of the target’s depth distribution, and (3) the estimation of a target’s change of shape through the temporal evolution of its segmented silhouette allows. Finally, we provide an in-depth analysis of the factors affecting the throughput and precision of our proposed tracker and perform extensive comparative analysis. Both the MATLAB and C++ versions of our software are available in the public domain. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1007/s11554-016-0654-3 | Journal of Real-time Image Processing |
Keywords | Field | DocType |
RGB-D tracking, Correlation filters, Scale and shape changes handling, Occlusion detection, Depth-based segmentation | Computer vision,MATLAB,Computer science,Silhouette,Segmentation,Fourier transform,Exploit,Software,Artificial intelligence,RGB color model,Throughput | Journal |
Volume | Issue | ISSN |
16 | 5 | 1861-8219 |
Citations | PageRank | References |
5 | 0.44 | 6 |
Authors | ||
8 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sion L. Hannuna | 1 | 69 | 10.37 |
| massimo camplani | 2 | 286 | 18.08 |
| Jake Hall | 3 | 6 | 0.79 |
| Majid Mirmehdi | 4 | 955 | 96.94 |
| Dima Damen | 5 | 225 | 31.54 |
| Tilo Burghardt | 6 | 55 | 9.22 |
| Adeline Paiement | 7 | 61 | 7.88 |
| Lili Tao | 8 | 109 | 8.69 |