Name
Abstract | ||
|---|---|---|
The Visual Object Tracking challenge VOT2016 aims at comparing short-term single-object visual trackers that do not apply pre-learned models of object appearance. Results of 70 trackers are presented, with a large number of trackers being published at major computer vision conferences and journals in the recent years. The number of tested state-of-the-art trackers makes the VOT 2016 the largest and most challenging benchmark on short-term tracking to date. For each participating tracker, a short description is provided in the Appendix. The VOT2016 goes beyond its predecessors by (i) introducing a new semi-automatic ground truth bounding box annotation methodology and (ii) extending the evaluation system with the no-reset experiment. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1007/978-3-319-48881-3_54 | ICCV Workshops |
Keywords | Field | DocType |
Performance evaluation,Short-term single-object trackers,VOT | Signal processing,Computer vision,BitTorrent tracker,Annotation,Computer graphics (images),Visualization,Computer science,Video tracking,Artificial intelligence,Benchmark (computing),Bounding overwatch | Conference |
Volume | ISSN | Citations |
9914 | 0302-9743 | 158 |
PageRank | References | Authors |
3.53 | 114 | 139 |