The goal of this article is to review the state-of-the-art tracking methods, classify them into
different categories, and identify new trends. Object tracking, in general, is a challenging …

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 …

Online streaming feature selection (OSFS) has attracted extensive attention during the past
decades. Current approaches commonly assume that the feature space of fixed data …

Today, artificial intelligence is everywhere in people's daily lives. Visual tracking, which is
used to identify and continuously track specific targets, is an important research domain in …

While color information is known to provide rich discriminative clues for visual inference,
most modern visual trackers limit themselves to the grayscale realm. Despite recent efforts to …

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 …

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 …

In this paper, we present a simple yet fast and robust algorithm which exploits the dense
spatio-temporal context for visual tracking. Our approach formulates the spatio-temporal …

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 …

In this paper, we develop a new approach of spatially supervised recurrent convolutional
neural networks for visual object tracking. Our recurrent convolutional network exploits the …