There is a large variety of trackers, which have been proposed in the literature during the
last two decades with some mixed success. Object tracking in realistic scenarios is a difficult …

Robust object tracking is a challenging task in computer vision. To better solve the partial
occlusion issue, part-based methods are widely used in visual object trackers. However, due …

This paper presents a novel locality sensitive histogram algorithm for visual tracking. Unlike
the conventional image histogram that counts the frequency of occurrences of each intensity …

Online learning has shown to be successful in tracking-by-detection of previously unknown
objects. However, most approaches are limited to a bounding-box representation with fixed …

The problem of visual tracking evaluation is sporting a large variety of performance
measures, and largely suffers from lack of consensus about which measures should be used …

The mean-shift procedure is a popular object tracking algorithm since it is fast, easy to
implement and performs well in a range of conditions. We address the problem of scale …

Over these years, Correlation Filter-based Trackers (CFTs) have aroused increasing
interests in the field of visual object tracking, and have achieved extremely compelling …

This paper addresses the problem of tracking objects which undergo rapid and significant
appearance changes. We propose a novel coupled-layer visual model that combines the …

A novel system for detection and tracking of vehicles from a single car-mounted camera is
presented. The core of the system are high-performance vision algorithms: the WaldBoost …

In this paper, we present the ALIEN tracking method that exploits oversampling of local
invariant representations to build a robust object/context discriminative classifier. To this …