Studies show lots of advanced research on various data types such as image, speech, and
text using deep learning techniques, but nowadays, research on video processing is also an …

Video surveillance systems obtain a great interest as application-oriented studies that have
been growing rapidly in the past decade. The most recent studies attempt to integrate …

Intrusion detection systems (IDSs) must be capable of detecting new and unknown attacks,
or anomalies. We study the problem of building detection models for both pure anomaly …

With advances in consumer electronics, demands have increased for greater granularity in
differentiating and analyzing human daily activities. Moreover, the potential of machine …

In this work, we have presented an end-to-end multi-person multi-camera tracking (MPMCT)
surveillance system and implemented it on edge analytics platform for real-time …

Detection of stationary foreground objects (ie, moving objects that remain static throughout
several frames) has attracted the attention of many researchers over the last decades and …

This paper presents a novel robust people counting system based on fusing the depth and
vision data. Conventional algorithms utilize the monoscopic or stereoscopic vision data to …

According to the real-living environment, radar-based human activity recognition (HAR) is
dedicated to recognizing and classifying a sequence of activities rather than individual …

Tracking of moving objects in pan-tilt-zoom (PTZ) cameras is a critical feature for automated
surveillance applications. The PTZ auto tracking function enables the camera to control its …

Currently, efficient and accurate key frame extraction for massive videos remains a
challenge, especially in surveillance applications. To overcome the inaccuracy of traditional …