Background modeling has emerged as a popular foreground detection technique for various
applications in video surveillance. Background modeling methods have become increasing …

Instance segmentation requires a large number of training samples to achieve satisfactory
performance and benefits from proper data augmentation. To enlarge the training set and …

We present a survey on maritime object detection and tracking approaches, which are
essential for the development of a navigational system for autonomous ships. The electro …

We propose a novel reconstruction-based transfer learning method called latent sparse
domain transfer (LSDT) for domain adaptation and visual categorization of heterogeneous …

Background modeling and foreground detection are important steps in video processing
used to detect robustly moving objects in challenging environments. This requires effective …

Background subtraction is often used as the first step in video analysis and smart
surveillance applications. However, the issue of inconsistent performance across different …

In recent years, background subtraction techniques have been used in vision and image
applications for moving target detection. However, most methods cannot provide fine results …

Background subtraction is a basic problem for change detection in videos and also the first
step of high-level computer vision applications. Most background subtraction methods rely …

The uncertainty of target sizes and the complexity of backgrounds are the main reasons for
the poor detection performance of small infrared targets. Focusing on this issue, this paper …

The information acquisition and automatic processing technology based on visual
surveillance sensors in intelligent transportation system (ITS) has become an important …