Local descriptors based face recognition engine for video surveillance systems

2013 ◽  
Author(s):  
Jiri Prinosil
Keyword(s):  
Face Recognition ◽  
Video Surveillance ◽  
Surveillance Systems ◽  
Local Descriptors

scholarly journals A deep learning approach to building an intelligent video surveillance system

2020 ◽  
Author(s):  
Jie Xu
Keyword(s):  
Face Recognition ◽  
Object Detection ◽  
Video Surveillance ◽  
Surveillance System ◽  
Video Surveillance System ◽  
Surveillance Systems ◽  
Single Shot ◽  
Convolutional Networks ◽  
Starting Point ◽  
Intelligent Video Surveillance System

Abstract Recent advances in the field of object detection and face recognition have made it possible to develop practical video surveillance systems with embedded object detection and face recognition functionalities that are accurate and fast enough for commercial uses. In this paper, we compare some of the latest approaches to object detection and face recognition and provide reasons why they may or may not be amongst the best to be used in video surveillance applications in terms of both accuracy and speed. It is discovered that Faster R-CNN with Inception ResNet V2 is able to achieve some of the best accuracies while maintaining real-time rates. Single Shot Detector (SSD) with MobileNet, on the other hand, is incredibly fast and still accurate enough for most applications. As for face recognition, FaceNet with Multi-task Cascaded Convolutional Networks (MTCNN) achieves higher accuracy than advances such as DeepFace and DeepID2+ while being faster. An end-to-end video surveillance system is also proposed which could be used as a starting point for more complex systems. Various experiments have also been attempted on trained models with observations explained in detail. We finish by discussing video object detection and video salient object detection approaches which could potentially be used as future improvements to the proposed system.

Application of robust face recognition in video surveillance systems

2018 ◽  
Vol 14 (2) ◽  
pp. 152-155 ◽  
Author(s):  
De-xin Zhang ◽  
Peng An ◽  
Hao-xiang Zhang
Keyword(s):  
Face Recognition ◽  
Video Surveillance ◽  
Surveillance Systems ◽  
Robust Face Recognition

scholarly journals Sistemas de reconocimiento facial, como herramienta para la búsqueda de personas

2017 ◽  
Vol 1 (8) ◽  
Author(s):  
Alex Gregorio Mendoza Arteaga ◽  
Gregorio Isoldo Mendoza Cedeño ◽  
Enrique Javier Macías Arias ◽  
Sandy Raúl Chun Molina
Keyword(s):  
Face Recognition ◽  
Key Words ◽  
Video Surveillance ◽  
Facial Recognition ◽  
Surveillance Systems ◽  
Biometric Recognition ◽  
Recognition Algorithms ◽  
Methods And Techniques ◽  
Automatic Systems ◽  
The Ideal

En el presente artículo se analiza la factibilidad de la implementación de algoritmos de reconocimiento facial integrados a los sistemas de video vigilancia de un territorio, para la localización de personas y como herramienta de búsqueda de individuos prófugos de la justicia convirtiéndose en un aporte importante a las investigaciones policiales y judiciales. Para alcanzar este objetivo, se estudian aristas sobre el reconocimiento biométrico y se considera el reconocimiento facial como el proceso ideal para la propuesta y discusión del artículo, en consecuencia, se investiga las etapas, métodos y técnicas más comunes y de mayor eficacia en los sistemas automáticos de reconocimiento de rostros para identificación de personas mediante imágenes y videos. Por consiguiente, se concluye que la implementación de un sistema automático de reconocimiento faciales interconectado a uno o varios sistemas de video vigilancia facilitara la búsqueda de individuos dentro del territorio donde se lo aplique.   Palabras claves: Biométrico, algoritmos, sistemas automáticos, tecnologías    Sistema de reconocimiento Facial    Systems of facial recognition, like tool for people's quest  Abstract In this article the feasibility of implementing facial recognition algorithms integrated video surveillance systems in a territory, to locate people tool analyzes and as individuals search for fugitives from justice becoming an important contribution to the police and judicial investigations. To achieve this goal, edges on biometric recognition are studied and considered facial recognition as the ideal for the proposal and discussion of Article process, therefore the steps, methods and techniques more common and more effective is investigated on the automatic face recognition to identify people through images and videos. Therefore, it is concluded that the implementation of a system of interconnected automatic facial recognition of one or several video surveillance systems facilitate finding individuals within the territory where it is applied.  Key words: Biometric, algorithms, automatic systems, technologies  

scholarly journals Secure Video Surveillance Framework in Smart City

Sensors ◽  
2021 ◽  
Vol 21 (13) ◽  
pp. 4419
Author(s):  
Hao Li ◽  
Tianhao Xiezhang ◽  
Cheng Yang ◽  
Lianbing Deng ◽  
Peng Yi
Keyword(s):  
Video Surveillance ◽  
Smart City ◽  
Key Management ◽  
Surveillance System ◽  
Chinese Remainder Theorem ◽  
Smart Cities ◽  
Group Key Management ◽  
Video Surveillance System ◽  
Surveillance Systems ◽  
Key Update

In the construction process of smart cities, more and more video surveillance systems have been deployed for traffic, office buildings, shopping malls, and families. Thus, the security of video surveillance systems has attracted more attention. At present, many researchers focus on how to select the region of interest (RoI) accurately and then realize privacy protection in videos by selective encryption. However, relatively few researchers focus on building a security framework by analyzing the security of a video surveillance system from the system and data life cycle. By analyzing the surveillance video protection and the attack surface of a video surveillance system in a smart city, we constructed a secure surveillance framework in this manuscript. In the secure framework, a secure video surveillance model is proposed, and a secure authentication protocol that can resist man-in-the-middle attacks (MITM) and replay attacks is implemented. For the management of the video encryption key, we introduced the Chinese remainder theorem (CRT) on the basis of group key management to provide an efficient and secure key update. In addition, we built a decryption suite based on transparent encryption to ensure the security of the decryption environment. The security analysis proved that our system can guarantee the forward and backward security of the key update. In the experiment environment, the average decryption speed of our system can reach 91.47 Mb/s, which can meet the real-time requirement of practical applications.

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