Deep Embedding for Face Recognition in Public Video Surveillance

2017 ◽  
pp. 31-39
Author(s):  
Guan Wang ◽  
Yu Sun ◽  
Ke Geng ◽  
Shengguang Li ◽  
Wenjing Chen
Keyword(s):  
Face Recognition ◽  
Video Surveillance ◽  
Deep Embedding

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.

scholarly journals Efficient Detection of Occlusion prior to Robust Face Recognition

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Rui Min ◽  
Abdenour Hadid ◽  
Jean-Luc Dugelay
Keyword(s):  
Face Recognition ◽  
Facial Expression ◽  
Video Surveillance ◽  
Real World ◽  
State Of The Art ◽  
Efficient Detection ◽  
Art Works ◽  
Enormous Amount ◽  
Recognition Systems ◽  
Robust Face Recognition

While there has been an enormous amount of research on face recognition under pose/illumination/expression changes and image degradations, problems caused by occlusions attracted relatively less attention. Facial occlusions, due, for example, to sunglasses, hat/cap, scarf, and beard, can significantly deteriorate performances of face recognition systems in uncontrolled environments such as video surveillance. The goal of this paper is to explore face recognition in the presence of partial occlusions, with emphasis on real-world scenarios (e.g., sunglasses and scarf). In this paper, we propose an efficient approach which consists of first analysing the presence of potential occlusion on a face and then conducting face recognition on the nonoccluded facial regions based on selective local Gabor binary patterns. Experiments demonstrate that the proposed method outperforms the state-of-the-art works including KLD-LGBPHS, S-LNMF, OA-LBP, and RSC. Furthermore, performances of the proposed approach are evaluated under illumination and extreme facial expression changes provide also significant results.

scholarly journals Surveillance using Face Recognition in Smart Cities

2020 ◽  
Vol 9 (4) ◽  
pp. 2042-2047
Keyword(s):  
Face Recognition ◽  
Video Surveillance ◽  
Crime Rate ◽  
Smart Cities ◽  
Police Department ◽  
Indian Government ◽  
The Past ◽  
Time To Build ◽  
Voting System ◽  
The City

In this project safe city demonstrates how the security in India can be increased with the help of video surveillance using facial recognition. In the Aadhar Card database, the Indian Government has stored fingerprint and Iris details of every civilian in India. But the Indian Government is only using the Fingerprint details in the voting system to avoid fake votes. With the help of this project any person roaming in the city limit can be easily monitored. This will be a very useful technology for the Police Department of India to track the criminals and to reduce crime rate. Whenever a person or criminal is needed to be traced , the photo of the target is uploaded into the software. The uploaded photo will be cross-checked by the software with the videos captured from the surveillance cameras. It will then identify the person based on the percentage of accuracy to be matched. In the past 5 years Indian Government have made many cities into smart cities. But now it’s time to build safe cities for India.

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

Applying Face Recognition in Video Surveillance Security Systems

2019 ◽  
pp. 271-280 ◽  
Author(s):  
Bauyrzhan Omarov ◽  
Batyrkhan Omarov ◽  
Shirinkyz Shekerbekova ◽  
Farida Gusmanova ◽  
Nurzhamal Oshanova ◽  
...  
Keyword(s):  
Face Recognition ◽  
Video Surveillance ◽  
Security Systems
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