Varieties of biometric facial techniques for detecting offenders (original) (raw)
Related papers
Giving Crime the 'evo': Catching Criminals Using EvoFIT Facial Composites
2010
Facial composites are traditionally made by witnesses and victims describing and selecting parts of criminals' faces, but this method is hard to do and has been shown to be generally ineffective. We have been working on an alternative system called EvoFIT for the past 12 years. Much of the development for this system has been carried out in the laboratory but, more recently, police forces have been formally evaluating it in criminal investigations. The current paper describes three of these police audits. It was found that EvoFIT composites made from real eyewitnesses led to an overall arrest in 23.4% of cases, which is similar to a 24.5% correct naming level found by laboratory research. System performance therefore appears to be effective both using simulated testing procedures and in the hands of the intended user.
Biometrics:: A Look at Facial Recognition
2003
The research described in this report was conducted by RAND Public Safety and Justice for the Virginia State Crime Commission. RAND is a nonprofit institution that helps improve policy and decisionmaking through research and analysis. RAND ® is a registered trademark. RAND's publications do not necessarily reflect the opinions or policies of its research sponsors.
Security Journal, 2016
Following the deployment of strong biometric systems in forensic science (for example, finger/palmprints or DNA), additional weaker biometric data such as facial information, ear or gait, are making their way into police practices and judicial systems. Their introduction is not going without presenting new challenges because of their lower discrimination power (that is, their efficiency at distinguishing individuals). Current biometric systems are designed and deployed as stand-alone applications (operating on their own merit, detached from any other investigative information) and are not fit for purpose when dealing with less discriminating modalities such as faces. We posit in this article that, for these emergent modalities, a different framework, integrated with the policing strategy, is required. The proposed framework is designed to maximize the payoff of these modalities for investigation or intelligence purposes. The number of facial images of non-identified individuals of interest available to police forces is increasing. Their sources go from surveillance cameras, cameras from automated teller machine, personal devices and so on. We analyzed, between 2009 and 2013, data from a regional intelligence platform, used by the crime intelligence units and, show using real case examples, the potential of facial images for crime investigation and crime intelligence.
Catching Even More Offenders with EvoFIT Facial Composites
uclan.ac.uk
Facial composites are an investigative tool used by police to identify suspects of crime. Unfortunately, traditional methods to construct the face have rather low success rates. We have been developing a new recognition-based method called EvoFIT that requires eyewitnesses to select whole faces from arrays of alternatives. Both published laboratory research and existing police field-trials have found that EvoFIT produces images that are more identifiable than images from traditional systems. In the current paper, we present an evaluation of a more recent version of EvoFIT: in 2010, EvoFIT was deployed in 35 criminal investigations by Humberside police and these images directly led to identification of 21 suspects, equating to 60% success-quadruple the performance of the previous system used within the force. The evaluation also showed that identification of a suspect led to conviction in 29% of investigations (6 out of 21). Overall, a conviction occurred in 17% of cases involving use of an EvoFIT (6 out of 35). We also outline more recent developments which indicate that an arrest is now likely in three out of every four cases in which EvoFIT is used, and a conviction rate of one in five.
A CHALLENGING FACIAL RECOGNITION TECHNOLOGY FOR BIOMETRICS IDENTIFICATION
This article discusses Biometrics-based confirmation and distinguishing proof that is developing as an extraordinary test to deal with testing assignments to vast populace ID. Biometrics requires that the individual to be distinguished be physically present for the purpose of recognizable proof and depends on "something which you are or you do" to give better security, expanded proficiency and enhanced exactness. It defeats a portion of the constraints of the customary individual recognizable proof innovations, for example, ID cards and PIN (ID cards might be lost, stolen, overlooked or lost though PIN might be overlooked or speculated by the impostors from the conventional distinguishing proof techniques). Computerized biometrics manages physiological or behavioural attributes, for example, iris, confront and so on that can be utilized to validate a man's personality or build up a character from a database.
Catching more offenders with EvoFIT Facial Composites: Lab Research and Police Field Trials
2011
Often, the only evidence of an offender's identity comes from the memory of an eyewitness. For over 12 years, we have been developing software called EvoFIT to help eyewitnesses recover their memories of offenders' faces, to assist police investigations. EvoFIT requires eyewitnesses to repeatedly select from arrays of faces, with 'breeding', to 'evolve' a face. Recently, police forces have been formally evaluating EvoFIT in criminal cases. The current paper describes four such police audits. It is reported that EvoFIT composites directly led to an arrest in 25.4% of cases overall; the arrest rate was 38.5% for forces that used a newer, less detailed face-recall interview. These results are similar to those found in the laboratory using simulated procedures. Here, we also evaluate the impact of interviewing techniques and outline further work that has improved system performance.
IRJET, 2022
Face Recognition/Identification has been a fast thriving, challenging and interesting domain in real time applications. A large number of face recognition algorithms have been developed in the recent decades. It has diverse application areas like surveillance, security, entertainment etc. The software on face identification is useful in airports, banks, offices, educational institutions for screening the people who are entering and exiting these places. Most of the Countries like Germany, Australia, etc use this technology [1]. Authorities have placed booths for face identification at borders and customs for automating the control system for passport verification and this becomes an important achievement in the context of ongoing covid-19 pandemic. Human face is a dynamic object that has a large degree of variability in its appearance as facial features of every individual are different, and this makes face recognition a challenging and ready to improve problem in the computer vision field. As in the face recognition/identification field, accuracy and speed both play an important role as well as it is the main issue. The goal of this paper is to evaluate different techniques of face recognition and provide a better solution for image and videobased face detection with greater accuracy, better response time and a step forward in betterment of society and protection of the society.
Leveraging Facial Recognition Technology in Criminal Identification
Proceedings of the 2022 International Conference on Advancements in Interdisciplinary Research towards Smart and Sustainable Society (AIR2022)
Detecting and identifying a criminal is a time-consuming and complex task. Criminals have become more astute in recent years, leaving no genetic evidence or fingerprint traces at the crime site. Using state-of-the-art facial identification technology is a quick and simple option. Surveillance cameras are being deployed at most buildings and traffic signals for monitoring reasons, thanks to advancements in security technology. Perpetrators, offenders, runaways, and lost individuals can all be identified using the camera's video recordings. This article aims to provide a brief survey of current improvements in face recognition, as well as a complete overview of several approaches to incorporating face detection in criminal identification based on various application scenarios. We also look at the evolution of facial recognition and where it is now in this study. It gives an overview of the internal architecture of a typical face detection system. It also highlights the obstacles that will be faced in instilling facial recognition as well as approaches to improve it while taking various tradeoffs into account. It also identifies areas for future research in the incorporation of facial identification in a variety of sectors.
Forensic Face Recognition: A Survey
2010
Beside a few papers which focus on the forensic aspects of automatic face recognition, there is not much published about it in contrast to the literature on developing new techniques and methodologies for biometric face recognition. In this report, we review forensic facial identification which is the forensic experts" way of manual facial comparison. Then we review famous works in the domain of forensic face recognition. Some of these papers describe general trends in forensics [1], guidelines for manual forensic facial comparison and training of face examiners who will be required to verify the outcome of automatic forensic face recognition system . Some proposes theoretical framework for application of face recognition technology in forensics [3] and automatic forensic facial comparison . Bayesian framework is discussed in detail and it is elaborated how it can be adapted to forensic face recognition. Several issues related with court admissibility and reliability of system are also discussed. Until now, there is no operational system available which automatically compare image of a suspect with mugshot database and provide result usable in court. The fact that biometric face recognition can in most cases be used for forensic purpose is true but the issues related to integration of technology with legal system of court still remain to be solved. There is a great need for research which is multidisciplinary in nature and which will integrate the face recognition technology with existing legal systems. In this report we present a review of the existing literature in this domain and discuss various aspects and requirements for forensic face recognition systems particularly focusing on Bayesian framework.
Mark Andrejevic and Neil Selwyn (2022) Facial Recognition. Cambridge: Polity Press
Law, technology and humans, 2023
Authored by leading experts in facial recognition in Australia, Facial Recognition presents a comprehensive account of the diversified facial recognition technology (FRT) applications in multiple scenarios. Andrejevic and Selwyn draw on interesting contemporary examples, such as FRT usage by employers seeking to analyse a job applicant's compatibility, retail stores aiming to detect clients' satisfaction and preferences, and law enforcement and intelligence agencies. The book is neatly structured, consisting of a preface, the main body (comprising seven chapters) and an epilogue. The authors helpfully address FRT's main characteristics in the first two chapters, in addition to clarifying its historical development and delineating its essential concepts. 1 The third chapter focuses on analysing FRT's global application. 2 The fourth, fifth and sixth chapters scrutinise the pros and cons of the technology, seeking to understand its potential benefits and harms. 3 The last chapter critically evaluates FRT from an individual and societal point of view. 4 Finally, in the epilogue, the writers share their perspectives concerning possible future FRT deployment and implementation paths. 5 Considering the diversity of FRT problems extensively tackled in the book and the richness of the analysis, I have decided to narrow my focus in this book review to parts of the analysis that appealed to my interest as a legal scholar working on the deployment of FRT in Brazil.