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 …

In this paper, a new image fusion algorithm based on fourth order partial differential
equations and principal component analysis is introduced. This is for the first time fourth …

Object tracking based on single sensor image sequences is now proved to be insufficient
when facing complex challenging factors such as occlusions, background clutter …

Image fusion aims to integrate multiple images that contain complementary information into
a single image using an appropriate strategy. The fusion of infrared (IR) and visible (VIS) …

Lung segmentation using computed tomography (CT) images is important for diagnosing
various lung diseases. Currently, no lung segmentation method has been developed for …

In this paper, a novel relative object tracking algorithm using a convolutional neural network
is proposed aiming to boost the tracking performance. A two-layer convolutional neural …

The compressive tracking (CT) method is a simple yet efficient algorithm which compresses
the high-dimensional features into a low-dimensional space while preserving most of the …

Traditional target tracking algorithms based on single sensor images are not applicable in
some circumstances such as cross-background, similar appearance object, shadow and …

Multi-feature tracking is an interesting but challenging task. Many previous works just
consider the fusion of different features from identical spectral image or identical features …