453 research outputs found

    Towards automated visual surveillance using gait for identity recognition and tracking across multiple non-intersecting cameras

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    Despite the fact that personal privacy has become a major concern, surveillance technology is now becoming ubiquitous in modern society. This is mainly due to the increasing number of crimes as well as the essential necessity to provide secure and safer environment. Recent research studies have confirmed now the possibility of recognizing people by the way they walk i.e. gait. The aim of this research study is to investigate the use of gait for people detection as well as identification across different cameras. We present a new approach for people tracking and identification between different non-intersecting un-calibrated stationary cameras based on gait analysis. A vision-based markerless extraction method is being deployed for the derivation of gait kinematics as well as anthropometric measurements in order to produce a gait signature. The novelty of our approach is motivated by the recent research in biometrics and forensic analysis using gait. The experimental results affirmed the robustness of our approach to successfully detect walking people as well as its potency to extract gait features for different camera viewpoints achieving an identity recognition rate of 73.6 % processed for 2270 video sequences. Furthermore, experimental results confirmed the potential of the proposed method for identity tracking in real surveillance systems to recognize walking individuals across different views with an average recognition rate of 92.5 % for cross-camera matching for two different non-overlapping views.<br/

    Biometric walk recognizer. Research and results on wearable sensor-based gait recognition

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    Gait is a biometric trait that can allow user authentication, though being classified as a "soft" one due to a certain lack in permanence, and to sensibility to specific conditions. The earliest research relies on computer vision-based approaches, especially applied in video surveillance. More recently, the spread of wearable sensors, especially those embedded in mobile devices, which are able to capture the dynamics of the walking pattern through simpler 1D signals, has spurred a different research line. This capture modality can avoid some problems related to computer vision-based techniques, but suffers from specific limitations. Related research is still in a less advanced phase with respect to other biometric traits. However, the promising results achieved so far, the increasing accuracy of sensors, the ubiquitous presence of mobile devices, and the low cost of related techniques, make this biometrics attractive and suggest to continue the investigations in this field. The first Chapters of this thesis deal with an introduction to biometrics, and more specifically to gait trait. A comprehensive review of technologies, approaches and strategies exploited by gait recognition proposals in the state-of-the-art is also provided. After such introduction, the contributions of this work are presented in details. Summarizing, it improves preceding result achieved during my Master Degree in Computer Science course of Biometrics and extended in my following Master Degree Thesis. The research deals with different strategies, including preprocessing and recognition techniques, applied to the gait biometrics, in order to allow both an automatic recognition and an improvement of the system accuracy

    Recent Application in Biometrics

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    In the recent years, a number of recognition and authentication systems based on biometric measurements have been proposed. Algorithms and sensors have been developed to acquire and process many different biometric traits. Moreover, the biometric technology is being used in novel ways, with potential commercial and practical implications to our daily activities. The key objective of the book is to provide a collection of comprehensive references on some recent theoretical development as well as novel applications in biometrics. The topics covered in this book reflect well both aspects of development. They include biometric sample quality, privacy preserving and cancellable biometrics, contactless biometrics, novel and unconventional biometrics, and the technical challenges in implementing the technology in portable devices. The book consists of 15 chapters. It is divided into four sections, namely, biometric applications on mobile platforms, cancelable biometrics, biometric encryption, and other applications. The book was reviewed by editors Dr. Jucheng Yang and Dr. Norman Poh. We deeply appreciate the efforts of our guest editors: Dr. Girija Chetty, Dr. Loris Nanni, Dr. Jianjiang Feng, Dr. Dongsun Park and Dr. Sook Yoon, as well as a number of anonymous reviewers

    Human identification from video using advanced gait recognition techniques

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    The solutions proposed in this thesis contribute to improve gait recognition performance in practical scenarios that further enable the adoption of gait recognition into real world security and forensic applications that require identifying humans at a distance. Pioneering work has been conducted on frontal gait recognition using depth images to allow gait to be integrated with biometric walkthrough portals. The effects of gait challenging conditions including clothing, carrying goods, and viewpoint have been explored. Enhanced approaches are proposed on segmentation, feature extraction, feature optimisation and classification elements, and state-of-the-art recognition performance has been achieved. A frontal depth gait database has been developed and made available to the research community for further investigation. Solutions are explored in 2D and 3D domains using multiple images sources, and both domain-specific and independent modality gait features are proposed

    Biometrics in forensic science: challenges, lessons and new technologies

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    Biometrics has historically found its natural mate in Forensics. The first applications found in the literature and over cited so many times, are related to biometric measurements for the identification of multiple offenders from some of their biometric and anthropometric characteristics (tenprint cards) and individualization of offender from traces found on crime-scenes (e.g. fingermarks, earmarks, bitemarks, DNA). From sir Francis Galton, to the introduction of AFIS systems in the scientific laboratories of police departments, Biometrics and Forensics have been "dating" with alternate results and outcomes. As a matter of facts there are many technologies developed under the "Biometrics umbrella" which may be optimised to better impact several Forensic scenarios and criminal investigations. At the same time, there is an almost endless list of open problems and processes in Forensics which may benefit from the introduction of tailored Biometric technologies. Joining the two disciplines, on a proper scientific ground, may only result in the success for both fields, as well as a tangible benefit for the society. A number of Forensic processes may involve Biometric-related technologies, among them: Evidence evaluation, Forensic investigation, Forensic Intelligence, Surveillance, Forensic ID management and Verification.\ud The COST Action IC1106 funded by the European Commission, is trying to better understand how Biometric and Forensics synergies can be exploited within a pan-European scientific alliance which extends its scope to partners from USA, China and Australia.\ud Several results have been already accomplished pursuing research in this direction. Notably the studies in 2D and 3D face recognition have been gradually applied to the forensic investigation process. In this paper a few solutions will be presented to match 3D face shapes along with some experimental results

    Effectiveness of Multi-View Face Images and Anthropometric Data In Real-Time Networked Biometrics

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    Over the years, biometric systems have evolved into a reliable mechanism for establishing identity of individuals in the context of applications such as access control, personnel screening and criminal identification. However, recent terror attacks, security threats and intrusion attempts have necessitated a transition to modern biometric systems that can identify humans under unconstrained environments, in real-time. Specifically, the following are three critical transitions that are needed and which form the focus of this thesis: (1) In contrast to operation in an offline mode using previously acquired photographs and videos obtained under controlled environments, it is required that identification be performed in a real-time dynamic mode using images that are continuously streaming in, each from a potentially different view (front, profile, partial profile) and with different quality (pose and resolution). (2) While different multi-modal fusion techniques have been developed to improve system accuracy, these techniques have mainly focused on combining the face biometrics with modalities such as iris and fingerprints that are more reliable but require user cooperation for acquisition. In contrast, the challenge in a real-time networked biometric system is that of combining opportunistically captured multi-view facial images along with soft biometric traits such as height, gait, attire and color that do not require user cooperation. (3) Typical operation is expected to be in an open-set mode where the number of subjects that enrolled in the system is much smaller than the number of probe subjects; yet the system is required to generate high accuracy.;To address these challenges and to make a successful transition to real-time human identification systems, this thesis makes the following contributions: (1) A score-based multi- modal, multi-sample fusion technique is designed to combine face images acquired by a multi-camera network and the effectiveness of opportunistically acquired multi-view face images using a camera network in improving the identification performance is characterized; (2) The multi-view face acquisition system is complemented by a network of Microsoft Kinects for extracting human anthropometric features (specifically height, shoulder width and arm length). The score-fusion technique is augmented to utilize human anthropometric data and the effectiveness of this data is characterized. (3) The performance of the system is demonstrated using a database of 51 subjects collected using the networked biometric data acquisition system.;Our results show improved recognition accuracy when face information from multiple views is utilized for recognition and also indicate that a given level of accuracy can be attained with fewer probe images (lesser time) when compared with a uni-modal biometric system

    Development of an application for diagnosis, monitoring and rehabilitation of neurodegenerative diseases

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    The progress of healthcare over the last years led to an aging of the world population, increasing the prevalence of age-related diseases in the society, mainly neurodegenerative diseases. These pathologies currently affect more than 30 million people worldwide, and there is currently no cure for them. The high costs experienced by patients and their families are largely due to the individual monitoring performed by technicians. New technologies are providing alternatives for monitoring, diagnosis and rehabilitation of individuals with these diseases. This project includes the development of a web application which allows patients with neurodegenerative diseases to be monitored with less invasion and costs, enabling greater adherence. The application follows several examples from the literature for the construction of games, includes diagnostic assessments used in the medical field and promotes its use through gamification techniques. The construction of the web server used the Python language and the Flask framework because of the availability of useful modules, large supporting community and scalability. The software was specially designed for people with Parkinson’s disease, featuring a simple navigation between menus and an easy-to-use interface. The web application was named "Mentalist". The development of the application was followed by professional neurologists and the results obtained were guided by clinicians’ practice. According to these experts, the developed functionalities cover the most important aspects of diagnosis, monitoring and rehabilitation, making it a tool of high importance and applicability in daily clinical practiceA melhoria das condições de vida e dos cuidados de saúde nos últimos anos tem originado um envelhecimento da população mundial, aumentando a prevalência de doenças relacionadas com a idade. Neste grupo de doenças destacam-se as doenças neurodegenerativas, que afetam mais de 30 milhões de pessoas e não têm, atualmente, cura. Os elevados custos experienciados pelos pacientes e pelas suas famílias devem-se, em grande parte, ao acompanhamento individual realizado por técnicos. Novas tecnologias têm possibilitado alternativas para o acompanhamento, diagnóstico e reabilitação de indivíduos com estas doenças. Este projeto inclui o desenvolvimento de uma aplicação web que permite a monitorização de pacientes com menos invasão e custos, proporcionando uma maior adesão. A aplicação segue exemplos da literatura para a construção dos jogos, inclui questionários de diagnóstico utilizados no ramo médico e promove a sua utilização através de técnicas de gamificação. Foi utilizada a linguagem Python e o framework Flask para a construção do servidor devido à existência de módulos úteis, grande comunidade de desenvolvedores e escalabilidade. O software foi desenvolvido especialmente para pacientes com a doença de Parkinson, apresentando uma navegação simples entre menus e uma interface fácil de usar. A aplicação web foi denominada "Mentalist". O desenvolvimento da aplicação foi seguido por neurologistas profissionais e os resultados obtidos foram guiados pela experiência dos clínicos. De acordo com estes especialistas, as funcionalidades desenvolvidas contemplam os principais aspetos relativos ao diagnóstico, monitorização e reabilitação, tornando-a num instrumento de grande importância e aplicabilidade na prática clínica diári
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