This paper explores deep learning (DL) methods that are used or have the potential to be
used for traffic video analysis, emphasising driving safety for both autonomous vehicles and …

As the videos captured by hand-held cameras are often perturbed by high-frequency jitters,
stabilization of these videos is an essential task. Many video stabilization methods have …

Video stabilization can improve the visual quality of videos that have been captured on
mobile devices or other handheld cameras, which are more prone to shaking and motion …

Portable camera devices are commonly used in modern society. However, the videos
captured by such consumer electronics cameras usually exhibit heavy shake which affect …

Detecting moving objects from the video sequences has been treated as a challenging
computer vision task, since the problems of dynamic background, multi-scale moving objects …

The speeded-up robust features (SURFs) algorithm is the best and most efficient local
invariant feature algorithm for application to 2-D images and is widely applied in the fields of …

The existing size measurement systems cannot meet the requirements of non-contact
measurement tasks, and the main challenge is how to detect various objects and improve …

Since digital media has become increasingly popular, video processing has expanded in
recent years. Video processing systems require high levels of processing, which is one of …

This paper considers stabilizing traffic videos, which are recorded by cameras mounted on
moving vehicles. Compared with videos captured by hand-held cameras, traffic videos are …

With the rapid development of edge devices such as mobile phones, in the past decade,
many videos have appeared on the professional video website and they are easy to retrieve …