Over the past two decades, one-class classification (OCC) becomes very popular due to its
diversified applicability in data mining and pattern recognition problems. Concerning to …

The goal of this paper is to review the state-of-the-art progress on visual tracking methods,
classify them into different categories, as well as identify future trends. Visual tracking is a …

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 …

This paper investigates long-term tracking of unknown objects in a video stream. The object
is defined by its location and extent in a single frame. In every frame that follows, the task is …

With the rapid development in computer vision domain, research on object tracking has
directed more attention by scholars. Out of view (OV) is an important challenge often …

This paper proposes a novel method for tracking failure detection. The detection is based on
the Forward-Backward error, ie the tracking is performed forward and backward in time and …

This paper shows that the performance of a binary classifier can be significantly improved by
the processing of structured unlabeled data, ie data are structured if knowing the label of …

Visual tracking in unconstrained environments is very challenging due to the existence of
several sources of varieties such as changes in appearance, varying lighting conditions …

We introduce a real-time and calibration-free facial performance capture framework based
on a sensor with video and depth input. In this framework, we develop an adaptive PCA …

A novel system for long-term tracking of a human face in unconstrained videos is built on
Tracking-Learning-Detection (TLD) approach. The system extends TLD with the concept of a …