Object segmentation and object tracking are fundamental research areas in the computer
vision community. These two topics are difficult to handle some common challenges, such …

Object tracking is one of the most important components in numerous applications of
computer vision. While much progress has been made in recent years with efforts on sharing …

In this paper we present a tracker, which is radically different from state-of-the-art trackers:
we apply no model updating, no occlusion detection, no combination of trackers, no …

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 …

This paper tackles the task of semi-supervised video object segmentation, ie, the separation
of an object from the background in a video, given the mask of the first frame. We present …

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 …

It is a challenging task to develop effective and efficient appearance models for robust object
tracking due to factors such as pose variation, illumination change, occlusion, and motion …

We introduce an unsupervised, geodesic distance based, salient video object segmentation
method. Unlike traditional methods, our method incorporates saliency as prior for object via …

Sparse representation has been applied to visual tracking by finding the best candidate with
minimal reconstruction error using target templates. However most sparse representation …

Multiple Object Tracking (MOT) plays an important role in solving many fundamental
problems in video analysis and computer vision. Most MOT methods employ two steps …