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Adaptive tracking-by-detection methods are widely used in computer vision for tracking arbitrary objects. Current approaches treat the tracking problem as a classification task and use online learning techniques to update the object model. However, for these updates to happen one needs to convert the estimated object position into a set of labelled training(More)
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)
The Visual Object Tracking challenge 2014, VOT2014, aims at comparing short-term single-object visual trackers that do not apply pre-learned models of object appearance. Results of 38 trackers are 2 Authors Suppressed Due to Excessive Length presented. The number of tested trackers makes VOT 2014 the largest benchmark on short-term tracking to date. For(More)
Efficient keypoint-based object detection methods are used in many real-time computer vision applications. These approaches often model an object as a collection of keypoints and associated descriptors, and detection then involves first constructing a set of correspondences between object and image keypoints via descriptor matching, and subsequently using(More)
Primary adenocarcinoma of lung has replaced squamous cell carcinoma as the commonest histological subtype of lung cancer and the incidence of primary lung adenocarcinoma appears to be rising. Although the main factors behind this 'epidemic-like' situation are largely undiscovered, filter cigarettes appear to significantly contribute to this shift in the(More)
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