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Human actions are predominantly presented in 2D format in video surveillance scenarios, which hinders the accurate determination of action details not apparent in 2D data. Depth estimation can aid human action recognition tasks, enhancing ...

(1) A novel 2D human skeleton action recognition model with spatial constraints, named 2D‐SCHAR, is introduced to address the ambiguity and uncertainty associated with human action recognition in 2D surveillance videos. (2) These issues stem from the ...

The paper proposes a new approach for crowd movement type estimation in video by combining convolutional neural network and integral optical flow. At first, main notions of crowd detection and tracking are given. Secondly, crowd movement features ...

The surge in intelligent video surveillance systems for public safety has brought about technological advancements but poses challenges, including handling vast video data. Issues such as extraction, analysis, storage scarcity, and hyperconnectivity ...

Fire poses a significant threat to both lives and property, necessitating effective early detection measures. Despite challenges in identifying smoke and fire in their initial stages, we have devised a cost-efficient visual detection system. Early fire ...

Due to the robustness of skeleton data to human scale, illumination changes, dynamic camera views, and complex backgrounds, great progress has been made in skeleton‐based video anomaly detection in recent years. The spatio‐temporal graph ...

Since most of the abnormal events in the video are caused by human activities, we propose a brand‐new network, called as Spatio‐Temporal Enhanced Graph‐Transformer AutoEncoder (STEGT‐AE) to model normal patterns of human motion for detecting human‐...

Anomalous event recognition has a complicated definition in the complex background due to the sparse occurrence of anomalies. In this paper, we form a framework for classifying multiple anomalies present in video frames that happen in a context such as ...

Intelligent video analysis is a new application direction in computer vision. Aiming at the decline of abnormal intrusion detection accuracy caused by background change in the intelligent video analysis field, an anomaly detection method for monitoring ...

With the development of multimedia, video surveillance systems are becoming more popular. However, the current video surveillance systems have a general function and are unable to provide Intelligent perception.

We design an intelligent video ...

As violence has increased around the world, surveillance cameras are everywhere, and they are only going to get more ubiquitous. Due to the massive volume of video footage, automatic activity detection systems must be used to create an online ...

Videos, which are commonly used for violent detection. A deep learning architecture is presented in this work using four‐dimensional video‐level convolution neural networks. The proposed architecture includes residual blocks that are used with three‐...

Modern autonomous systems rely on both object detection and object tracking in their visual perception pipelines. Although many recent works have attacked the object detection component of autonomous vehicles, these attacks do not work on full pipelines ...

The automatic detection and tracking of appearance and behavior anomalies in video surveillance systems is one of the promising areas for the development and implementation of artificial intelligence. In this paper, we present a formalization of ...

Video‐based person re‐identification (Re‐ID) has received increasing attention in video surveillance analysis in recent years. To extract relevant information of the target, many existing methods utilise the attention mechanism in the residual ...

Person re-identification (re-ID) aims to recognize an identity in non-overlapping camera views. Recently, re-ID received increased attention due to the growth of deep learning and its prominent applications in the field of automated video surveillance. ...

In recent decades, the automatic video surveillance system has gained significant importance in computer vision community. The crucial objective of surveillance is monitoring and security in public places. In the traditional local binary pattern, the ...

• Finding matches for a person in a real-time surveillance video is challenging.
• ...

Surveillance of human activities in real time has drawn tremendous attention in the field of research. As manual monitoring of surveillance videos is expensive and prone to error, automation of surveillance is preferred. Person ...

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Intelligent video analysis from sources such as urban surveillance cameras is a prolific research area today. Multiple types of computer architectures offer a wide range of possibilities when addressing the needs of computer vision technologies. When it ...

Taxi safety incidents cause serious threats to the personal and property safety of drivers and passengers. An effective solution was installed video surveillance in taxis. For privacy issues and the cost of using equipment, only a few taxis were ...

Vision-based Automated Vehicle Recognition (VAVR) has attracted considerable attention recently. Particularly given the reliance on emerging deep learning methods, which have powerful feature extraction and pattern learning abilities, vehicle ...

The optimal placement of surveillance cameras and determining the configuration of exposure routes to ensure optimal coverage is essentially a combinatorial optimisation problem. In this paper, we proposed two approaches to identify and locate the ...

In the modern world, suicide is one of the ten leading causes of population deaths. According to the forecast, in 2020 suicide will come out on the second place in the world as a cause of death, yielding only to cardiovascular diseases. The problem of ...