In the recent past, the number of surveillance cameras placed in the public has increased significantly, and an enormous amount of visual data is produced at an alarming rate. Resultantly, there is a demand for a distributed system for video analytic...
The exponential growth of video data across domains such as surveillance, transportation, and healthcare has raised critical challenges in scalability, real-time processing, and privacy preservation. While existing studies have addressed individual a...
The falling cost of IoT cameras, the advancement of AI-based computer vision algorithms, and powerful hardware accelerators for deep learning have enabled the widespread deployment of surveillance cameras with the ability to automatically analyze str...
The paper presents a comprehensive overview of intelligent video analytics and human action recognition methods. The article provides an overview of the current state of knowledge in the field of human activity recognition, including various techniqu...
The use of lightweight drones has surged in recent years across both personal and commercial applications, necessitating the ability to conduct live video analytics on drones with limited computational resources. While edge computing offers a solutio...
The automated analysis of pool game videos presents significant challenges due to complex object interactions, precise rule requirements, and event-driven game dynamics that traditional computer vision approaches struggle to address effectively. This...
A variety of tools are available to collect, process and analyse learning data obtained from the clickstream generated by students watching learning resources in video format. There is also some literature on the uses of such data in order to better...
In smart city scenarios, the huge proliferation of monitoring cameras scattered in public spaces has posed many challenges to network and processing infrastructure. A few dozen cameras are enough to saturate the city’s backbone. In addition, mo...
Modern video surveillance systems mainly rely on human operators to monitor and interpret the behavior of individuals in real time, which may lead to severe delays in responding to an emergency. Therefore, there is a need for continued research into...
Technology and innovation empower higher educational institutions (HEI) to use different types of learning systems—video learning is one such system. Analyzing the footprints left behind from these online interactions is useful for understandin...
In edge-assisted low-latency video analytics, a critical challenge is balancing on-device inference latency against the high bandwidth costs and network delays of offloading. Ineffectively managing this trade-off degrades performance and hinders crit...
The primary purpose of video surveillance is to monitor public indoor areas or the boundaries of secure facilities to safeguard them against theft, unauthorized access, fire, and various other potential threats. Security cameras, equipped with integr...
The digitization of production systems has revolutionized industrial monitoring. Analyzing real-time bottom-up data enables the dynamic monitoring of industrial processes. Data are collected in various types, like video frames and time signals. This...
Edge computing is the best approach for meeting the exponential demand and the real-time requirements of many video analytics applications. Since most of the recent advances regarding the extraction of information from images and video rely on comput...
Railway networks systems are by design open and accessible to people, but this presents challenges in the prevention of events such as terrorism, trespass, and suicide fatalities. With the rapid advancement of machine learning, numerous computer visi...
In recent years, the amount of intelligent CCTV cameras installed in public places for surveillance has increased enormously and as a result, a large amount of video data is produced every moment. Due to this situation, there is an increasing request...
The increasing development of urban centers brings serious challenges for traffic management. In this paper, we introduce a smart visual sensor, developed for a pilot project taking place in the Australian city of Liverpool (NSW). The project’s...
Operational modal analysis (OMA) is required for the maintenance of large-scale civil structures. This paper developed a novel methodology of non-contact-based blind identification of the modal frequency of a vibrating structure from its video measur...
In the standardization of versatile video coding (VVC), discrete cosine transform (DCT)-2, discrete sine transform (DST)-7, and DCT-8 are regarded as the primary transform kernels. However, DST-4 and DCT-4 can also be considered as the transform kern...
In the last decade, the differences in the information communication technology (ICT) infrastructures between urban and rural areas have registered a tremendous increase. ICT infrastructures could strongly help rural communities where many operations...
Intelligent video analytics systems have come to play an essential role in many fields, including public safety, transportation safety, and many other industrial areas, such as automated tools for data extraction, and analyzing huge datasets, such as...
Traffic analyses, particularly speed measurements, are highly valuable in terms of road safety and traffic management. In this paper, an analytical model is presented to measure the speed of a moving vehicle using an off-the-shelf video camera. The m...
Driver drowsiness is a major contributor to road accidents, often resulting from delayed reaction times and impaired cognitive performance. This study introduces EffRes-DrowsyNet, a hybrid deep learning model that integrates the architectural efficie...
Students’ affective states describe their engagement, concentration, attitude, motivation, happiness, sadness, frustration, off-task behavior, and confusion level in learning. In online learning, students’ affective states are determinati...
Today, video analytics are becoming extremely popular due to the increasing need for extracting valuable information from videos available in public sharing services through camera-driven streams in IoT environments. To avoid data communication overh...
Short-form video platforms have become an important marketing channel for library resources and services. However, such promotions’ actual performance is not as good as expected. This research examined the performance of library marketing on th...
With the growing prevalence of large-scale intelligent surveillance camera systems, the burden on real-time video analytics pipelines has significantly increased due to continuous video transmission from numerous cameras. To mitigate this strain, rec...
Blockage of culverts by transported debris materials is reported as the salient contributor in originating urban flash floods. Conventional hydraulic modeling approaches had no success in addressing the problem primarily because of the unavailability...
Ensuring citizens’ safety and security has been identified as the number one priority for city authorities when it comes to the use of smart city technologies. Automatic understanding of the scene, and the associated provision of situational aw...
Intelligent video surveillance systems detect pre-configured surveillance events through background modeling, foreground and object extraction, object tracking, and event detection. Shadow regions inside video frames sometimes appear as foreground ob...
The increased global waste generation rates over the last few decades have made the waste management task a significant problem. One of the potential approaches adopted globally is to recycle a significant portion of generated waste. However, the con...
Smart city is an area where the Internet of things is used effectively with sensors. The data used by smart city can be collected through the cameras, sensors etc. Intelligent video surveillance (IVS) systems integrate multiple networked cameras for...
This study proposes an edge-centric outdoor parking management system that performs on-site inference on a low-power embedded device and outputs slot-level occupancy decisions in real time. A dataset comprising 13,691 images was constructed using two...
Introduction: Narrow band imaging (NBI) video bronchoscopy provides better visualisation of submucosal vascular patterns in malignant airway lesions compared to white light bronchoscopy. This analytical cross-sectional study was aimed to look for any...
The flipped classroom has been increasingly employed as a pedagogical strategy in the higher education classroom. This approach commonly involves pre-class learning activities that are delivered online through learning management systems that collect...
Recent advances in sensor technologies, in particular video-based human detection, object tracking and pose estimation, have opened new possibilities for the automatic or semi-automatic per-frame annotation of sport videos. In the case of racket spor...
In recent decades, the Variational AutoEncoder (VAE) model has shown good potential and capability in image generation and dimensionality reduction. The combination of VAE and various machine learning frameworks has also worked effectively in differe...
Higher educational institutes (HEI) are adopting ubiquitous and smart equipment such as mobile devices or digital gadgets to deliver educational content in a more effective manner than the traditional approaches. In present works, a lot of smart clas...
Movies have become one of the major sources of entertainment in the current era, which are based on diverse ideas. Action movies have received the most attention in last few years, which contain violent scenes, because it is one of the undesirable fe...
This study presents the validation of the Player Personality and Dynamics Scale (PPDS), designed to identify player profiles in educational gamification contexts with narrative elements. Through a sample of 635 participants, a questionnaire was devel...
Deep neural network-based computer vision applications have exploded and are widely used in intelligent services for IoT devices. Due to the computationally intensive nature of DNNs, the deployment and execution of intelligent applications in smart s...
Mental health issues are a growing problem worldwide, and their detection can be complicated. Assessments such as the Patient Health Questionnaire (PHQ-9) and Generalized Anxiety Disorder (GAD-7) questionnaire can be useful tools for detecting depres...
We introduce a robust and light-weight multi-image super-resolution restoration (SRR) method and processing system, called OpTiGAN, using a combination of a multi-image maximum a posteriori approach and a deep learning approach. We show the advantage...
Large sports stadiums require robust real-time monitoring due to high crowd density, complex spatial configurations, and limited network infrastructure. This research evaluates a hybrid edge–cloud architecture implemented in a national stadium...
CCTV safety monitoring demands anomaly detectors combine reliable clip-level accuracy with predictable per-clip latency despite weak supervision. This work investigates compact vision–language models (VLMs) as practical detectors for this regim...
This paper proposes a transfer learning-based approach to enhance video-driven safety risk detection in industrial environments, addressing the critical challenge of limited generalization across diverse operational scenarios. Conventional deep learn...
In the road transport network, intersections are among the most critical locations leading to a risk of death and serious injury. The traditional methods to assess the safety of intersections are based on statistical analyses that require crash data....
Video streaming-based real-time vehicle identification and license plate recognition systems are challenging to design and deploy in terms of real-time processing on edge, dealing with low image resolution, high noise, and identification. This paper...
Temporal action detection (TAD) aims to recognize actions as well as their corresponding time spans from an input video. While techniques exist that accurately recognize actions from manually trimmed videos, current TAD solutions often struggle to id...
Communication between Deaf and hearing individuals remains a persistent challenge requiring attention to foster inclusivity. Despite notable efforts in the development of digital solutions for sign language recognition (SLR), several issues persist,...
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