Visual object tracking has attracted widespread interests recently. Due to the complementary
features provided by visible and infrared images, fusion tracking based on visible and …

Visual tracking is a fundamental task in computer vision with significant practical
applications in various domains, including surveillance, security, robotics, and human …

Integrating multiple different yet complementary feature representations has been proved to
be an effective way for boosting tracking performance. This paper investigates how to …

In this paper, we propose a novel graph model, called weighted sparse representation
regularized graph, to learn a robust object representation using multispectral (RGB and …

In this paper, we present a moving object detection system named Flux Tensor with Split
Gaussian models (FTSG) that exploits the benefits of fusing a motion computation method …

Visual surveillance is an active research topic in image processing. Transit systems are
actively seeking new or improved ways to use technology to deter and respond to accidents …

With a large number of video surveillance systems installed for the requirement from
industrial security, the task of object tracking, which aims to locate objects of interest in …

To intelligently analyze and understand video content, a key step is to accurately perceive
the motion of the interested objects in videos. To this end, the task of object tracking, which …

Currently sparse signal reconstruction gains considerable interest and is applied in many
fields. In this paper, a similarity induced by joint sparse representation is designed to …

Tracking target of interests is an important step for motion perception in intelligent video
surveillance systems. While most recently developed tracking algorithms are grounded in …