Fusion of Face Recognition Algorithms for Video-Based Surveillance Systems

2003 ◽  
pp. 235-249 ◽  
Author(s):  
Gian Luca Marcialis ◽  
Fabio Roli
Keyword(s):  
Face Recognition ◽  
Surveillance Systems ◽  
Recognition Algorithms

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 Illumination Normalization Algorithm Combination Analysis in Face Recognition

2017 ◽  
Vol 9 (3) ◽  
pp. 334-339
Author(s):  
Rokas Semėnas
Keyword(s):  
Face Recognition ◽  
Large Scale ◽  
Real Life ◽  
Direct Approach ◽  
Small Scale ◽  
Test Results ◽  
Illumination Normalization ◽  
Recognition Algorithms ◽  
Life Problems

Face recognition programs have many practical usages in various fields, such as security or entertainment. Existing recognition algorithms must deal with various real life problems – mainly with illumination. In practice, illumination normalization models are often used only for Small-scale futures extraction, ignoring Large-scale features. In this article, new and more direct approach to this problem is offered, used algorithms and test results are given.

scholarly journals Effective Descriptors based Face Recognition Technique for Robotic Surveillance Systems

2018 ◽  
Vol 133 ◽  
pp. 968-975 ◽  
Author(s):  
Vinay A ◽  
Aditi R Deshpande ◽  
Pranathi B S ◽  
Harshita Jha ◽  
K N Balasubramanya Murthy ◽  
...  
Keyword(s):  
Face Recognition ◽  
Surveillance Systems ◽  
Recognition Technique

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.

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