Surveillance System for Intruder Detection Using Facial Recognition

Subject UK biometrics strategy. Significance One component of the United Kingdom’s biometrics surveillance system, facial recognition technology, faces landmark legal action. Yet this addresses just one aspect of a larger problem: the collection and use of biometrics of millions of UK citizens, including children, poses a dangerous data protection risk -- one that would have no solution in the event of a breach. Impacts Unlike a username or password, raw biometric data cannot be reset, so collecting it poses a grave data protection risk. Schools are unlikely to have strong cybersecurity protection, making children’s biometrics a target for a data breach. There is little transparency about what companies are building the biometric system and their track record with data protection. Companies selling facial recognition technology will use fears about its inaccuracy to call for more data to train their models.

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A study on implementation of real-time intelligent video surveillance system based on embedded module

EURASIP Journal on Image and Video Processing ◽

10.1186/s13640-021-00576-0 ◽

2021 ◽

Vol 2021 (1) ◽

Author(s):

Jin Su Kim ◽

Min-Gu Kim ◽

Sung Bum Pan

Keyword(s):

Real Time ◽

Video Surveillance ◽

Surveillance System ◽

Fire Detection ◽

Fall Detection ◽

Video Surveillance System ◽

Surveillance Systems ◽

Intelligent Video Surveillance ◽

Intruder Detection ◽

Intelligent Video Surveillance System

AbstractConventional surveillance systems for preventing accidents and incidents do not identify 95% thereof after 22 min when one person monitors a plurality of closed circuit televisions (CCTV). To address this issue, while computer-based intelligent video surveillance systems have been studied to notify users of abnormal situations when they happen, it is not commonly used in real environment because of weakness of personal information leaks and high power consumption. To address this issue, intelligent video surveillance systems based on small devices have been studied. This paper suggests implement an intelligent video surveillance system based on embedded modules for intruder detection based on information learning, fire detection based on color and motion information, and loitering and fall detection based on human body motion. Moreover, an algorithm and an embedded module optimization method are applied for real-time processing. The implemented algorithm showed performance of 88.51% for intruder detection, 92.63% for fire detection, 80% for loitering detection and 93.54% for fall detection. The result of comparison before and after optimization about the algorithm processing time showed 50.53% of decrease, implying potential real-time driving of the intelligent image monitoring system based on embedded modules.

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Perceptual Effects and Recollective Experience in Face Recognition

Experimental Psychology (formerly Zeitschrift für Experimentelle Psychologie) ◽

10.1027/1618-3169.52.3.224 ◽

2005 ◽

Vol 52 (3) ◽

pp. 224-231 ◽

Cited By ~ 7

Author(s):

Chrisanthi Nega

Keyword(s):

Face Recognition ◽

Recognition Memory ◽

Congruency Effect ◽

Facial Recognition ◽

Memory Systems ◽

Study Time ◽

Perceptual Fluency ◽

Recollective Experience ◽

Trace Strength ◽

Size Congruency

Abstract. Four experiments were conducted investigating the effect of size congruency on facial recognition memory, measured by remember, know and guess responses. Different study times were employed, that is extremely short (300 and 700 ms), short (1,000 ms), and long times (5,000 ms). With the short study time (1,000 ms) size congruency occurred in knowing. With the long study time the effect of size congruency occurred in remembering. These results support the distinctiveness/fluency account of remembering and knowing as well as the memory systems account, since the size congruency effect that occurred in knowing under conditions that facilitated perceptual fluency also occurred independently in remembering under conditions that facilitated elaborative encoding. They do not support the idea that remember and know responses reflect differences in trace strength.

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