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Toward Fast and Accurate Violence Detection for Automated video Surveillance Applications

IEEE ACCESS 2023年 11卷 18772-18793页

作者： Huszar, Viktor Denes Adhikarla, Vamsi Kiran Negyesi, Imre Krasznay, Csaba Natl Univ Publ Serv Fac Mil Sci & Officer Training H-1083 Budapest Hungary Pazmany Peter Catholic Univ Fac Informat Technol & Bion H-1083 Budapest Hungary

Surveillance cameras are increasingly being used worldwide due to the proliferation of digital video capturing, storage, and processing technologies. However, the large volume of video data generated makes it difficult for humans to perform real-time analysis, and even manual approaches can result in delayed detection of events. Automatic violence detection in surveillance footage has therefore gained significant attention in the scientific community as a way to address this challenge. With the advancement of machine learning algorithms, automatic video recognition tasks such as violence detection have become increasingly feasible. In this study, we investigate the use of smart networks that model the dynamic relationships between actors and/or objects using 3D convolutions to capture both the spatial and temporal structure of the data. We also leverage the knowledge learned by a pre-trained action recognition model for efficient and accurate violence detection in surveillance footage. We extend and evaluate several public datasets featuring diverse and challenging video content to assess the effectiveness of our proposed methods. Our results show that our approach outperforms state-of-the-art methods, achieving approximately a 2% improvement in accuracy with fewer model parameters. Additionally, our experiments demonstrate the robustness of our approach under common compression artifacts encountered in remote server processing applications.

关键词： Anomaly detection anomaly localization automated video surveillance deep learning efficient violence detection human activity recognition security smart cities video recognition violence detection

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Cloud Computing’s Effect on video Games Streaming 2

Cloud Computing’s Effect on Video Games Streaming

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2nd International Conference on Automation, Computing and Renewable Systems, ICACRS 2023

作者： Komathi, A. Lenin, J. Asha, S. Suresh, A. Suguna, M. Srinivasan, C. Department of Computer Science Nadar Saraswathi College of Arts and Science College Tamilnadu Theni India Department of ComputerScience and Engineering Alliance College of Engineering and Design Alliance University Karnataka Bengaluru India Department of Information Technology S.A. Engineering College Tamil Nadu Chennai India Department of Computer Science and Engineering Siddharth Institute of Engineering & Technology Andhra Pradesh Puttur India Tamil Nadu Salem India Department of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Tamil Nadu Chennai India

ISBN: (纸本)9798350340235

The disruptive power of cloud computing is altering the gaming industry. Real-time gaming is now feasible because to advancements in streaming algorithms, further blurring the lines between the digital and physical worlds. Understanding the potential of Cloud computing to change the gaming industry is the emphasis which investigates the complicated relationship between numerous technologies. By using cutting-edge streaming protocols and techniques like Adaptive Bitrate Streaming (ABS), buffering, caching, and compression, users may have uninterrupted, high-quality gaming experiences. The study's findings herald a new era of interactive entertainment and shed light on the transformative possibilities of these technologies. Asynchronous Bit-Rate (ABR) encoding, buffering, caching algorithms, video compression standards, and streaming protocols are just few of the numerous digital components that work together to provide uninterrupted data transmission. The rapid progress of ABR algorithms has made it possible to dynamically alter video quality to maximize the user experience across a broad variety of network scenarios. Buffering and caching algorithms play crucial roles by proactively managing data flow and storage to avoid disruptions in the streaming experience. © 2023 IEEE.

关键词： Autism buffering algorithms caching methods Cloud Computing Impact Interactive Entertainment Standards for video compression Streaming algorithms streaming protocols video Games

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On the Performance of video Super Resolution algorithms for HTTP-based Adaptive Streaming Applications 46

On the Performance of Video Super Resolution Algorithms for ...

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Applications of digital Image Processing XLVI 2023

作者： Barman, Nabajeet Reznik, Yuriy Martini, Maria Kingston University London United Kingdom Brightcove Inc. Seattle United States

ISBN: (纸本)9781510665620

Recent years have seen tremendous growth and advancement in the field of super-resolution algorithms for both images and videos. Such algorithms are mainly based on deep learning technologies and are primarily used for upsampling lower resolution images and videos, often outperforming existing traditional upsampling algorithms. Using such advanced upscaling algorithms on the client side can result in significant bandwidth and storage savings as the client can simply request lower-resolution images/videos and then upscale them to the required (higher) display resolution. However, the performance analysis of such proposed algorithms has been limited to a few datasets which are not representative of modern-era adaptive bitrate video streaming applications. Also, many times they only consider scaling artefacts, and hence their performance when considering typical compression artefacts is not known. In this paper, we evaluate the performance of such AI-based upscaling algorithms on different datasets considering a typical adaptive streaming system. Different content types, video compression standards and renditions are considered. Our results indicate that the performance of video upsampling algorithms measured objectively in terms of PSNR and SSIM is insignificant compared to traditional upsampling algorithms. However, more detailed analysis in terms of other advanced quality metrics as well as subjective tests are required for a comprehensive evaluation. © 2023 SPIE.

关键词： Deep learning

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Improved Image compression Using Bi-branch Transformer-CNN Feature Extractor Network

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International Journal of Network Security 2025年第3期27卷 586-593页

作者： Wu, Weimei Hu, Jianhua Zeng, Wenying Guangdong Polytechnic of Science and Technology Guangdong Zhuhai519090 China

With the wide application of digital images, lossy image compression technology has become an important method for storage and transmission. However, the pursuit of high compression ratios also highlights artifacts in compression. To address this, a new dual-channel image de-artifacting method is proposed. This approach combines the advantages of Convolutional Neural Networks (CNNs) and Transformer models to precisely capture high-frequency and low-frequency elements in the image, thereby improving the denoising effects. The experimental results show that the advantages of image de-artifacting can improve image quality effectively and significantly. In addition, the latest advancements in Transformer technology in image restoration are exploited to highlight its powerful capability in processing global information. The findings can provide important guidance and motivation for advancing research and developing more effective compression techniques. © (2025), (International Journal of Network Security). All rights reserved.

关键词： Convolutional neural networks

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Advanced Method for Compressing digital Images as a Part of video Stream to Pre-processing of UAV Data Before Encryption

Advanced Method for Compressing Digital Images as a Part of ...

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作者： Hu, Zhengbing Ryabyy, Myroslav Prystavka, Pylyp Gnatyuk, Sergiy Janisz, Karina Proskurin, Dmytro Hubei University of Technology Hongshan Wuhan430068 China National Aviation University 1 Liubomyra Huzara Avenue Kyiv03058 Ukraine University of Applied Sciences in Nowy Sącz 1 Staszica Street Nowy Sącz33-300 Poland

Reducing the volume of video and photo information while maintaining high-quality visual perception remains an urgent task that specialists in specific subject areas are constantly working on. However, without questioning the success of the developers of compression methods (both lossy and lossless), reducing the size during streaming of video information carries a deterioration in the quality of information that is quite noticeable to the human eye or distorts the information in such a way that its further processing becomes impossible. In the work, a basic method to increase the level (percentage) of compression of a digital image (as a part of the video stream) with losses was proposed, and it is based on both transformations that ensure the invariance of that digital image and background extraction methods. The main value of result is that a high level of compression was demonstrated. Future study will be related to the universal dataset of crypto-algorithms development as well as AI/ML subsystem formation. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Unmanned aerial vehicles (UAV)

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Fast Intra Prediction Algorithm for AVS3 8th

Fast Intra Prediction Algorithm for AVS3

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8th International Conference on Signal and Information Processing, Network and Computers, ICSINC 2021

作者： Fang, Lingfeng Sun, Songlin Liu, Rui National Engineering Laboratory for Mobile Network Security Beijing University of Posts and Telecommunications Beijing China Ministry of Education Beijing University of Posts and Telecommunications Beijing China School of Information and Communication Engineering Beijing University of Posts and Telecommunication Beijing China San Jose State University San JoseCA95192 United States

ISBN: (纸本)9789811933868

With the development of 5G and multimedia technologies, applications such as ultra-high-definition video, VR and High dynamic range video have become more popular. This has led to an increasing amount of video data, which has brought great challenges to the storage and transmission of video data. Therefore, a video encoder with better compression performance is needed to remove the time redundancy, spatial redundancy and statistical redundancy in the image sequence of video, and greatly compress the raw video data under the premise of ensuring image quality. The Audio video Coding Standard Workgroup of China has formulated the AVS video coding standard, and the latest AVS3 standard is currently under research and formulation. In order to improve the compression performance of the encoder, AVS3 introduced a large number of new technologies on the basis of AVS2 standard, resulting in a 266% increase in encoding complexity compared to AVS2. This paper optimizes the coding unit partition process and intra mode decision process of AVS3 Results show that the proposed algorithms reduce about 46.82% and 4.49% intra encoding time on average, with only 1.22% and 0.01% increases in terms of BDBR. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： digital storage

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Scalable MDC-Based Volumetric video Delivery for Real-Time One-to-Many WebRTC Conferencing 24

Scalable MDC-Based Volumetric Video Delivery for Real-Time O...

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15th ACM Multimedia Systems Conference (ACM MMSys)

作者： De Fre, Matthias van der Hooft, Jeroen Wauters, Tim De Turck, Filip Univ Ghent Imec IDLab Ghent Belgium

ISBN: (纸本)9798400704123

The production and consumption of video content has become a staple in the current day and age. With the rise of virtual reality (VR), users are now looking for immersive, interactive experiences which combine the classic video applications, such as conferencing or digital concerts, with newer technologies. By going beyond 2D video into a 360 degree experience the first step was made. However, a 360 degree video offers only rotational movement, making interaction with the environment difficult. Fully immersive 3D content formats, such as light fields and volumetric video, aspire to go further by enabling six degrees-of-freedom (6DoF), allowing both rotational and positional freedom. Nevertheless, the adoption of immersive video capturing and rendering methods has been hindered by their substantial bandwidth and computational requirements, rendering them in most cases impractical for low latency applications. Several efforts have been made to alleviate these problems by introducing specialized compression algorithms and by utilizing existing 2D adaptation methods to adapt the quality based on the user's available bandwidth. However, even though these methods improve the quality of experience (QoE) and bandwidth limitations, they still suffer from high latency which makes real-time interaction unfeasible. To address this issue, we present a novel, open source [32], one-to-many streaming architecture using point cloud-based volumetric video. To reduce the bandwidth requirements, we utilize the Draco codec to compress the point clouds before they are transmitted using WebRTC which ensures low latency, enabling the streaming of real-time 6DoF interactive volumetric video. Content is adapted by employing a multiple description coding (MDC) strategy which combines sampled point cloud descriptions based on the estimated bandwidth returned by the Google congestion control (GCC) algorithm. MDC encoding scales more easily to a larger number of users compared to performing indi

关键词： Volumetric video Adaptive Streaming WebRTC Virtual Conferencing Multiple Description Coding Virtual Reality

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High-resolution image compression algorithms in remote sensing imaging

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DISPLAYS 2023年第1期79卷

作者： Ma, Xianghe Shanghai Maritime Univ Coll Informat Engn Shanghai Peoples R China

digital image processing (DIP) has great application values in many fields, especially in remote sensing image processing, which represents the acquisition, enhancement, analysis, encoding, transmission, and storage of remote sensing images. With the development of chip technology and parallel computing technology, various digital image processing technologies have been successfully applied to satellite applications to help researchers exploit reliable information from remote-sensing images. However, the huge amount of images generated by ultra-high resolution optical remote sensing satellites put great pressure on existing transmission, storage, and processing technologies. Therefore, this paper proposes a spatio-temporal compression pipeline for remote sensing images based on lossy compression methods with ultra-high compression ratios to reduce the overhead required for the transmission and storage of remote sensing images while maintaining the quality of the compressed images. The experimental results show that the proposed method outperforms the classical image compression such as JPEG-2000.

关键词： Remote sensing Image compression video compression

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digital video Manipulation Detection Technique Based on compression algorithms

arXiv

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arXiv 2024年

作者： Fernández, Edgar González Orozco, Ana Lucila Sandoval Villalba, Luis Javier García INFOTEC Center for Research and Innovation in Information and Communication Technologies Aguascalientes20313 Mexico Madrid28040 Spain

digital images and videos play a very important role in everyday life. Nowadays, people have access the affordable mobile devices equipped with advanced integrated cameras and powerful image processing applications. Technological development facilitates not only the generation of multimedia content, but also the intentional modification of it, either with recreational or malicious purposes. This is where forensic techniques to detect manipulation of images and videos become essential. This paper proposes a forensic technique by analysing compression algorithms used by the H.264 coding. The presence of recompression uses information of macroblocks, a characteristic of the H.264-MPEG4 standard, and motion vectors. A Vector Support Machine is used to create the model that allows to accurately detect if a video has been recompressed. © 2024, CC BY-NC-SA.

关键词： Support vector machines

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Mobile Devices and Multimedia: Enabling technologies, algorithms, and Applications 2022

Mobile Devices and Multimedia: Enabling Technologies, Algori...

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IS and T International Symposium on Electronic Imaging: Mobile Devices and Multimedia: Enabling technologies, algorithms, and Applications, MOBMU 2022

The proceedings contain 154 papers. The topics discussed include: feature-driven 3d range geometry compression via spatially-aware depth encoding;open source deep learning inference libraries for autonomous driving systems;problems in image target-based color correction;improvement of aerial image by simulations;recognition-aware learned image compression;artist-specific style transfer for semantic segmentation of paintings: the value of large corpora of surrogate artworks;data visualization of crime data using immersive virtual reality;a comparison of non-experts and experts using DSIS method;contrast enhancement: cross-modal learning approach for medical images;a continuous bitstream-based blind video quality assessment using multi-layer perceptron;correspondences for image and video reconstruction;design and analysis on low-power and low-noise single slope ADC for digital pixel sensors;incremental two-network approach to develop a purity analyzer system for canola seeds;advantage of machine learning over maximum likelihood in limited-angle low-photon x-ray tomography;image montage detection based on image segmentation and robust hashing techniques;chatbot integrated with machine learning deployed in the cloud and performance evaluation;and the relationship between vision and simulated remote vision system air refueling performance.

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