Relevant bibliographies by topics / Video surveillance system

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Video surveillance system'

Author: Grafiati
Published: 4 June 2021
Last updated: 25 July 2025

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Journal articles on the topic "Video surveillance system"

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A M, Darshan. "Intelligent Video Surveillance System." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 04 (2024): 1–5. http://dx.doi.org/10.55041/ijsrem31409.

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Intelligent Video Surveillance Systems (IVSS) have emerged as critical tools for ensuring safety and security in various environments. This paper presents an IVSS capable of real-time detection and analysis of critical events, including falls and vehicle crashes. The proposed system employs state-of-the-art deep learning techniques, specifically the YOLO (You Only Look Once) object detection algorithm, to analyze video streams obtained from diverse sources such as surveil- lance cameras and recorded videos. For fall detection, the system utilizes the aspect ratio of detected persons’ bounding
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Kamble, Prof Kirti K., Prof Rahul G. Deshmukh, and Prof Bhavana Shinde. "A Fast Browsing System with Colour Image Enhancement for Surveillance Videos." International Journal for Research in Applied Science and Engineering Technology 12, no. 5 (2024): 2895–902. http://dx.doi.org/10.22214/ijraset.2024.62203.

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Abstrac: Surveillance cameras have been widely installed in large cities to monitor and record human activities for different applications. Since surveillance cameras often record all events 24 hours/day, it necessarily takes huge workforce watching surveillance videos to search for specific targets,thus a system that helps the user quickly look for targets of interest is highly demanded. This paper proposes a quick surveillance video browsing system with colour image enhancement. The basic idea is to collect all of moving objects which carry the most significant information in surveillance vi
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DJ, Neal, and (Shawon) Rahman Syed. "Video Surveillance in the Cloud?" International Journal on Cryptography and Information Security (IJCIS) 2, no. 3 (2019): 1–19. https://doi.org/10.5281/zenodo.3358616.

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A high-resolution video surveillance management system incurs huge amounts of storage and network bandwidth. The current infrastructure required to support a high-resolution video surveillance management system (VMS) is expensive and time consuming to plan, implement and maintain. With the recent advances in cloud technologies, opportunity for the utilization of virtualization and the opportunity for distributed computing techniques of cloud storage have been pursued on the basis to find out if the various cloud computing services that are available can support the current requirements to a hi
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Praveen, Dabbara. "Intelligent Video Surveillance System." International Journal for Research in Applied Science and Engineering Technology 9, no. VIII (2021): 741–43. http://dx.doi.org/10.22214/ijraset.2021.37399.

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Intelligent video recognition with in-depth learning concept will create a self-paced video analytics program. CCTV cameras are used in all areas where safety is paramount. Manual monitoring seems tedious and time-consuming. Security can be defined by different words in different contexts such as identity theft, violence, explosions etc. Security monitoring is a tedious and time-consuming task. In this project we will analyse video feeds in real time and identify any unusual items such as violence or theft. The concept of in-depth learning simulates the functioning of the human brain in proces
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Al-Asadi, Tawfiq A., and Salah H. Al-bohader. "Surveillance System based on GIS and Video Film." Journal of Advanced Research in Dynamical and Control Systems 11, no. 10-SPECIAL ISSUE (2019): 701–7. http://dx.doi.org/10.5373/jardcs/v11sp10/20192860.

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Agrawal, Priyanka. "Smart Surveillance System using Face Tracking." International Journal for Research in Applied Science and Engineering Technology 9, no. VI (2021): 2613–17. http://dx.doi.org/10.22214/ijraset.2021.35567.

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The face is seen as a key component of the human body, and humans utilise it to identify one another. Face detection in video refers to the process of detecting a person's face from a video sequence, while face tracking refers to the process of tracking the person's face throughout the video. Face detection and tracking has become a widely researched issue due to applications such as video surveillance systems and identifying criminal activity. However, working with videos is tough due to problems such as bad illumination, low resolution, and atypical posture, among others. It is critical to p
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Babli, Kumari, Jaiswal Rachit, Kumar Kshitij, Mohit Rai, and Singh Kumar. "Automated CCTV Surveillance System." Journal of Optoelectronics and Communication 5, no. 1 (2023): 36–41. https://doi.org/10.5281/zenodo.7885340.

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<em>Automated video surveillance systems are becoming increasingly common in a wide range of settings, from public spaces and transportation systems to retail stores and residential buildings. These systems use advanced computer vision and machine learning algorithms to automatically detect, track, and classify objects in video streams, and they can provide valuable information and alerts for security, surveillance, and other applications.</em><em>&nbsp;</em><em>In this paper, we present a survey of the state-of-the-art technologies and applications of automated video surveillance systems. We
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M, Mr Nandish. "Protecting Privacy in Surveillance Systems via Selective Video Encryption." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 05 (2024): 1–5. http://dx.doi.org/10.55041/ijsrem34554.

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The "Privacy Preservation in Surveillance Video Using Selective Encryption" study addresses the issue of privacy in surveillance videos. Video surveillance systems are widely deployed in many public places such as banks, supermarkets, airports, roads, and residential areas. However, the privacy of individuals in these videos is a major concern. The proposed system aims to conceal faces while not interfering with the observation and recognition of human activities. The system uses selective encryption to encrypt only the face region of the frames while other parts of the frame are retained as i
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S.Sivasubramaniam, Dr.M.Ramanan. "DETECTING EVENTS IN VIDEO SURVEILLANCE SYSTEM." Journal For Innovative Development in Pharmaceutical and Technical Science https://jidps.com/ 2, no. 12 (2020): 21–25. https://doi.org/10.5281/zenodo.3600020.

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Multimedia systems utilize multiple media streams, each of which has different confidence levels in accomplishing various detection tasks. For example, in a multimedia surveillance system, one would usually have higher confidence in an audio stream compared to a video stream for detecting human shouting events. The pre-computation of these confidence levels is cumbersome especially when new media streams are dynamically added to the system. This paper proposes a novel method, which dynamically computes the confidence levels of new streams based on the past history of their agreement/disagreeme
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Nguyen, Cuong, Wu-chi Feng, and Feng Liu. "Hotspot: Making computer vision more effective for human video surveillance." Information Visualization 15, no. 4 (2016): 273–85. http://dx.doi.org/10.1177/1473871616630015.

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Studies have shown that the human capability of monitoring multiple surveillance videos is limited. Computer vision techniques have been developed to detect abnormal events to support human video surveillance; however, their results are often unreliable, thus distracting surveillance operators and making them miss important events. This article presents Hotspot as a surveillance video visualization system that can effectively leverage noisy computer vision techniques to support human video surveillance. Hotspot consists of two views: a designated focus view to summarize videos with detected ev
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Dissertations / Theses on the topic "Video surveillance system"

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Haida, Maksim, and Максим Володимирович Гайда. "Video surveillance system of target contour." Thesis, National Aviation University, 2021. https://er.nau.edu.ua/handle/NAU/50751.

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1. Программирование компьютерного зрения на языке Python / Ян Эрик Солем, пер. с англ. Слинкин А.А. – М.: ДМК Пресс, 2016. – 312.с.: ил. 2. Системи відеоспостереження та методи виділення контурів на зображеннях / K. Гжешчик, Д. Загородня, А. Саченко, Б. Русин – «Управління проектами та розвиток виробництва», 2018, №3(67). 3. Advances in Computer Vision and Pattern Recognition / Giovanni Maria Farinella, Sebastiano Battiato, Roberto Cipolla – Springer-Verlag London 2013. 4. Детекторы углов. URL: https://habr.com/ru/post/244541/ (дата звернення: 23.02.2021).<br>Computer vision is the science
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Zou, Zichuan. "Remote Client of Home Video Surveillance System." Case Western Reserve University School of Graduate Studies / OhioLINK, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=case1459453065.

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Zhou, Han, and 周晗. "Intelligent video surveillance in a calibrated multi-camera system." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2011. http://hub.hku.hk/bib/B45989217.

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Luo, Ning. "A Wireless Traffic Surveillance System Using Video Analytics." Thesis, University of North Texas, 2011. https://digital.library.unt.edu/ark:/67531/metadc68005/.

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Video surveillance systems have been commonly used in transportation systems to support traffic monitoring, speed estimation, and incident detection. However, there are several challenges in developing and deploying such systems, including high development and maintenance costs, bandwidth bottleneck for long range link, and lack of advanced analytics. In this thesis, I leverage current wireless, video camera, and analytics technologies, and present a wireless traffic monitoring system. I first present an overview of the system. Then I describe the site investigation and several test links with
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Abdelkader, Mohamed F. "Integration and evaluation of a video surveillance system." College Park, Md. : University of Maryland, 2005. http://hdl.handle.net/1903/2817.

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Thesis (M.S.) -- University of Maryland, College Park, 2005.<br>Thesis research directed by: Dept. of Electrical and Computer Engineering. Title from t.p. of PDF. Includes bibliographical references. Published by UMI Dissertation Services, Ann Arbor, Mich. Also available in paper.
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Tuvskog, Johanna. "Evaluation of Face Recognition Accuracy in Surveillance Video." Thesis, Linköpings universitet, Datorseende, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-166758.

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Automatic Face Recognition (AFR) can be useful in the forensic field when identifying people in surveillance footage. In AFR systems it is common to use deep neural networks which perform well if the quality of the images keeps a certain level. This is a problem when applying AFR on surveillance data since the quality of those images can be very poor. In this thesis the CNN FaceNet has been used to evaluate how different quality parameters influence the accuracy of the face recognition. The goal is to be able to draw conclusions about how to improve the recognition by using and avoiding certai
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Tanase, Cristina-Madalina. "Multi-person tracking system for complex outdoor environments." Thesis, Uppsala universitet, Institutionen för informationsteknologi, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-245082.

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The thesis represents the research in the domain of modern video tracking systems and presents the details of the implementation of such a system. Video surveillance is a high point of interest and it relies on robust systems that interconnect several critical modules: data acquisition, data processing, background modeling, foreground detection and multiple object tracking. The present work analyzes different state of the art methods that are suitable for each module. The emphasis of the thesis is on the background subtraction stage, as the final accuracy and performance of the person tracking
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Sutor, S. R. (Stephan R. ). "Large-scale high-performance video surveillance." Doctoral thesis, Oulun yliopisto, 2014. http://urn.fi/urn:isbn:9789526205618.

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Abstract The last decade was marked by a set of harmful events ranging from economical crises to organized crime, acts of terror and natural catastrophes. This has led to a paradigm transformation concerning security. Millions of surveillance cameras have been deployed, which led to new challenges, as the systems and operations behind those cameras could not cope with the rapid growth in number of video cameras and systems. Looking at today’s control rooms, often hundreds or even thousands of cameras are displayed, overloading security officers with irrelevant information. The purpose of this
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Sinn, Richard M. Eng Massachusetts Institute of Technology. "Virtual pan-tilt-zoom for a wide-area-video surveillance system." Thesis, Massachusetts Institute of Technology, 2008. http://hdl.handle.net/1721.1/46489.

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Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2008.<br>Includes bibliographical references (p. 95).<br>Advancements in the CMOS Image Sensor have enabled very high-performance, high resolution imaging systems to be built at relatively low cost. The availability of high-pixel count video imaging systems that can cover a wide field-of-view enables a surveillance technique called Virtual Pan-Tilt-Zoom. Virtual Pan-Tilt-Zoom provides the same functional properties as a mechanical pan-tilt-zoom setup, but it does not suffer from the p
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Diratie, Eyassu Dilla. "Hybrid internet of things network for energy-efficient video surveillance system." Electronic Thesis or Diss., université Paris-Saclay, 2022. http://www.theses.fr/2022UPASG066.

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Les réseaux de capteurs visuels sans fil basés sur les réseaux maillés IEEE 802.11 sont des solutions efficaces et adaptées aux systèmes de vidéosurveillance pour surveiller les intrusions dans des zones sélectionnées. Les réseaux de capteurs visuels basés sur IEEE 802.11 offrent des transmissions vidéo à haut débit mais souffrent de problèmes d'inefficacité énergétique. De plus, la transmission vidéo dans les réseaux de capteurs visuels nécessite une qualité de service (QoS) stricte en termes de bande passante et de délai. En outre, il est difficile de réduire la consommation énergétique glob
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Books on the topic "Video surveillance system"

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Osuna, Alex. IBM System Storage N series and digital video surveillance. IBM, International Technical Support Organization, 2008.

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Dufour, Jean-Yves, ed. Intelligent Video Surveillance Systems. John Wiley & Sons, Inc., 2012. http://dx.doi.org/10.1002/9781118577851.

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Remagnino, Paolo, Graeme A. Jones, Nikos Paragios, and Carlo S. Regazzoni, eds. Video-Based Surveillance Systems. Springer US, 2002. http://dx.doi.org/10.1007/978-1-4615-0913-4.

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Dufour, Jean-Yves. Intelligent video surveillance systems. ISTE, 2013.

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Regazzoni, Carlo S., Gianni Fabri, and Gianni Vernazza, eds. Advanced Video-Based Surveillance Systems. Springer US, 1999. http://dx.doi.org/10.1007/978-1-4615-5085-3.

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Foresti, Gian Luca, Petri Mähönen, and Carlo S. Regazzoni, eds. Multimedia Video-Based Surveillance Systems. Springer US, 2000. http://dx.doi.org/10.1007/978-1-4615-4327-5.

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A, Velastin Sergio, Remagnino Paolo 1963-, and Institution of Electrical Engineers, eds. Intelligent distributed video surveillance systems. Institution of Electrical Engineers, 2006.

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Regazzoni, Carlo S. Advanced Video-Based Surveillance Systems. Springer US, 1999.

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S, Regazzoni Carlo, Fabri Gianni, Vernazza Gianni, and Workshop on Advanced Video Based Surveillance (1998 : Genoa, Italy), eds. Advanced video-based surveillance systems. Kluwer Academic Publishers, 1999.

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Nilsson, Fredrik. Intelligent network video: Understanding modern video surveillance systems. Taylor & Francis, 2008.

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Book chapters on the topic "Video surveillance system"

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Durak, Nurcan, Adnan Yazici, and Roy George. "Online Surveillance Video Archive System." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/978-3-540-69423-6_37.

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Venkatesan, R., P. Dinesh Anton Raja, and A. Balaji Ganesh. "Video Surveillance Based Tracking System." In Advances in Intelligent Systems and Computing. Springer India, 2014. http://dx.doi.org/10.1007/978-81-322-2126-5_41.

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Rajesh, T. M., and Kavyashree Dalawai. "Automated Video Surveillance System Using Video Analytics." In Intelligent Computing and Communication. Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-1084-7_43.

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Cucchiara, R., C. Grana, G. Neri, M. Piccardi, and A. Prati. "The Sakbot System for Moving Object Detection and Tracking." In Video-Based Surveillance Systems. Springer US, 2002. http://dx.doi.org/10.1007/978-1-4615-0913-4_12.

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Chang, Ting-Hsun, and Shaogang Gong. "Bayesian Modality Fusion for Tracking Multiple People with a Multi-Camera System." In Video-Based Surveillance Systems. Springer US, 2002. http://dx.doi.org/10.1007/978-1-4615-0913-4_6.

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Siebel, N. T., and S. J. Maybank. "On the Use of Colour Filtering in an Integrated Real-Time People Tracking System." In Video-Based Surveillance Systems. Springer US, 2002. http://dx.doi.org/10.1007/978-1-4615-0913-4_14.

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Regazzoni, Carlo S., Claudio Sacchi, and Gianluca Gera. "Intelligence Distribution of a Third Generation People Counting System Transmitting Information Over an Urban Digital Radio Link." In Video-Based Surveillance Systems. Springer US, 2002. http://dx.doi.org/10.1007/978-1-4615-0913-4_21.

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Raggio, Marco, Ivano Barbieri, Alberto Cabitto, and Luís Corte-Real. "Scalable H.324 Video-Based Surveillance System." In Multimedia Video-Based Surveillance Systems. Springer US, 2000. http://dx.doi.org/10.1007/978-1-4615-4327-5_14.

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Senior, Andrew. "Privacy Protection in a Video Surveillance System." In Protecting Privacy in Video Surveillance. Springer London, 2009. http://dx.doi.org/10.1007/978-1-84882-301-3_3.

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Murphey, Yi L., Henry Lu, Robert Karlsen, Grant Gerhart, and Thomas Meitzler. "Dyta: An Intelligent System for Dynamic Target Analysis." In Multimedia Video-Based Surveillance Systems. Springer US, 2000. http://dx.doi.org/10.1007/978-1-4615-4327-5_11.

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Conference papers on the topic "Video surveillance system"

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Aryan, Ansh, Dharya Pratap Singh, and Nitish Kumar. "Intelligent Video Surveillance System." In 2024 International Conference on Expert Clouds and Applications (ICOECA). IEEE, 2024. http://dx.doi.org/10.1109/icoeca62351.2024.00170.

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Xu, Zhengya, and Hong Ren Wu. "Smart video surveillance system." In 2010 IEEE International Conference on Industrial Technology. IEEE, 2010. http://dx.doi.org/10.1109/icit.2010.5472694.

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Banu, Virgil Claudiu, Ilona Madalina Costea, Florin Codrut Nemtanu, and Iulian Badescu. "Intelligent video surveillance system." In 2017 IEEE 23rd International Symposium for Design and Technology in Electronic Packaging (SIITME). IEEE, 2017. http://dx.doi.org/10.1109/siitme.2017.8259891.

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Krishna, Arppitha, Neha Pendkar, Shruti Kasar, Umesh Mahind, and Shridhar Desai. "Advanced Video Surveillance System." In 2021 3rd International Conference on Signal Processing and Communication (ICPSC). IEEE, 2021. http://dx.doi.org/10.1109/icspc51351.2021.9451694.

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Huang, Hu, Benchang Zheng, Kai Cui, Dongdong Wang, Zhihao Wu, and Jia Zhang. "Passive video surveillance system." In International Symposium on Artificial Intelligence and Robotics 2021, edited by Shota Nakashima, Shenglin Mu, and Huimin Lu. SPIE, 2021. http://dx.doi.org/10.1117/12.2607203.

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Gao, Siyuan. "An Intelligent Video Surveillance System." In 2010 International Conference on E-Product E-Service and E-Entertainment (ICEEE 2010). IEEE, 2010. http://dx.doi.org/10.1109/iceee.2010.5661050.

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Khelvas, Alexander, Darya Demyanova, Alexander Gilya-Zetinov, Egor Konyagin, Roman Khafizov, and Ruslan Pashkov. "Adaptive distributed video surveillance system." In 2020 International Conference on Technology and Entrepreneurship - Virtual (ICTE-V). IEEE, 2020. http://dx.doi.org/10.1109/icte-v50708.2020.9113774.

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Hsu, Charles, and Harold Szu. "Smart sensing surveillance video system." In SPIE Commercial + Scientific Sensing and Imaging, edited by Liyi Dai, Yufeng Zheng, Henry Chu, and Anke D. Meyer-Bäse. SPIE, 2016. http://dx.doi.org/10.1117/12.2239982.

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Yu, Chen, Jianan Wang, Jiayuan Shan, and Ming Xin. "Multi-UAV UWA video surveillance system." In 2016 14th International Conference on Control, Automation, Robotics and Vision (ICARCV). IEEE, 2016. http://dx.doi.org/10.1109/icarcv.2016.7838810.

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Fang Li, Maylor K. H. Leung, Mehul Mangalvedhekar, and Mark Balakrishnan. "Automated video surveillance and alarm system." In 2008 International Conference on Machine Learning and Cybernetics (ICMLC). IEEE, 2008. http://dx.doi.org/10.1109/icmlc.2008.4620578.

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Reports on the topic "Video surveillance system"

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Jain, Ramesh. Multiple Perspective Interactive Video Surveillance and Monitoring System. Defense Technical Information Center, 2000. http://dx.doi.org/10.21236/ada379758.

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Тарасова, Олена Юріївна, and Ірина Сергіївна Мінтій. Web application for facial wrinkle recognition. Кривий Ріг, КДПУ, 2022. http://dx.doi.org/10.31812/123456789/7012.

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Facial recognition technology is named one of the main trends of recent years. It’s wide range of applications, such as access control, biometrics, video surveillance and many other interactive humanmachine systems. Facial landmarks can be described as key characteristics of the human face. Commonly found landmarks are, for example, eyes, nose or mouth corners. Analyzing these key points is useful for a variety of computer vision use cases, including biometrics, face tracking, or emotion detection. Different methods produce different facial landmarks. Some methods use only basic facial landmar
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