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The Visual Object Tracking challenge 2015, VOT2015, aims at comparing short-term single-object visual trackers that do not apply pre-learned models of object appearance. Results of 62 trackers are presented. The number of tested trackers makes VOT 2015 the largest benchmark on shortterm tracking to date. For each participating tracker, a short description(More)
Variations of target appearances due to illumination changes, heavy occlusions and abrupt motions are the major factors for tracking failures. In this paper, we show that these failures can be effectively handled by exploiting the trajectory consistency between the current tracker and its historical trained snapshots. Here, we propose a Scale-adaptive(More)
With the rapid development of computer technology, programming methods have changed a lot. Nowadays, software developing based on SOA (Service Oriented Architecture) is more and more popular due to its autonomous, distributed and reusable. And at the same time, user requirements are also changing, they are anxious for the information they want from the vast(More)
Robust feature representation plays significant role in visual tracking. However, it remains a challenging issue, since many factors may affect the experimental performance. The existing method which combine different features by setting them equally with the fixed weight could hardly solve the issues, due to the different statistical properties of(More)
Variations of target appearances due to illumination changes, heavy occlusions, and target deformations are the major factors for tracking drift. In this paper, we show that the tracking drift can be effectively corrected by exploiting the relationship between the current tracker and its historical tracker snapshots. Here, a multi-expert framework is(More)
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