Within the field of computer vision, change detection algorithms aim at automatically
detecting significant changes occurring in a scene by analyzing the sequence of frames in a …

According to the demographic evolution in industrialized countries, more and more elderly
people will experience falls at home and will require emergency services. The main problem …

Deep models have the risk of utilizing spurious clues to make predictions, eg, recognizing
actions via classifying the background scene. This problem severely degrades the open-set …

This paper presents an online highly accurate system for automatic number plate
recognition (ANPR) that can be used as a basis for many real-world ITS applications. The …

In this paper, we propose a people counting algorithm using an impulse radio ultra-
wideband radar sensor. The proposed algorithm is based on a strategy of understanding the …

Moving object detection has been a central topic of discussion in computer vision for its wide
range of applications like in self-driving cars, video surveillance, security, and enforcement …

A wide range of human–robot collaborative applications in diverse domains, such as
manufacturing, health care, the entertainment industry, and social interactions, require an …

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

Compressive sensing (CS) is an emerging field that provides a framework for image
recovery using sub-Nyquist sampling rates. The CS theory shows that a signal can be …

To achieve high-resolution 2-D images, through-wall imaging (TWI) radar with ultra-
wideband and long antenna arrays faces considerable technical challenges such as a …