Machine Learning Techniques For Gait Biometric Recognition PDF Download
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| Author | : James Eric Mason |
| Publisher | : Springer |
| Total Pages | : 247 |
| Release | : 2016-02-04 |
| Genre | : Technology & Engineering |
| ISBN | : 3319290886 |
Download Machine Learning Techniques for Gait Biometric Recognition Book in PDF, ePub and Kindle
This book focuses on how machine learning techniques can be used to analyze and make use of one particular category of behavioral biometrics known as the gait biometric. A comprehensive Ground Reaction Force (GRF)-based Gait Biometrics Recognition framework is proposed and validated by experiments. In addition, an in-depth analysis of existing recognition techniques that are best suited for performing footstep GRF-based person recognition is also proposed, as well as a comparison of feature extractors, normalizers, and classifiers configurations that were never directly compared with one another in any previous GRF recognition research. Finally, a detailed theoretical overview of many existing machine learning techniques is presented, leading to a proposal of two novel data processing techniques developed specifically for the purpose of gait biometric recognition using GRF. This book · introduces novel machine-learning-based temporal normalization techniques · bridges research gaps concerning the effect of footwear and stepping speed on footstep GRF-based person recognition · provides detailed discussions of key research challenges and open research issues in gait biometrics recognition · compares biometrics systems trained and tested with the same footwear against those trained and tested with different footwear
| Author | : Srikanta Patnaik |
| Publisher | : Springer Nature |
| Total Pages | : 853 |
| Release | : 2020-07-25 |
| Genre | : Technology & Engineering |
| ISBN | : 9811552436 |
Download Advances in Machine Learning and Computational Intelligence Book in PDF, ePub and Kindle
This book gathers selected high-quality papers presented at the International Conference on Machine Learning and Computational Intelligence (ICMLCI-2019), jointly organized by Kunming University of Science and Technology and the Interscience Research Network, Bhubaneswar, India, from April 6 to 7, 2019. Addressing virtually all aspects of intelligent systems, soft computing and machine learning, the topics covered include: prediction; data mining; information retrieval; game playing; robotics; learning methods; pattern visualization; automated knowledge acquisition; fuzzy, stochastic and probabilistic computing; neural computing; big data; social networks and applications of soft computing in various areas.
| Author | : IEEE Staff |
| Publisher | : |
| Total Pages | : |
| Release | : 2020-12-16 |
| Genre | : |
| ISBN | : 9781728196015 |
Download 2020 IEEE Pune Section International Conference (PuneCon) Book in PDF, ePub and Kindle
The scope of the conference includes Domains Tracks in the following key areas but not limited to only these areas The sessions are based on following fields and tracks, 1 Computer Vision and Machine Learning, 2 Electric vehicles, 3 Medical Signal Processing, 4 Assistive Technology, 5 Data Analytics
| Author | : Gaurav Jaswal |
| Publisher | : CRC Press |
| Total Pages | : 409 |
| Release | : 2021-03-22 |
| Genre | : Technology & Engineering |
| ISBN | : 1000291669 |
Download AI and Deep Learning in Biometric Security Book in PDF, ePub and Kindle
This book provides an in-depth overview of artificial intelligence and deep learning approaches with case studies to solve problems associated with biometric security such as authentication, indexing, template protection, spoofing attack detection, ROI detection, gender classification etc. This text highlights a showcase of cutting-edge research on the use of convolution neural networks, autoencoders, recurrent convolutional neural networks in face, hand, iris, gait, fingerprint, vein, and medical biometric traits. It also provides a step-by-step guide to understanding deep learning concepts for biometrics authentication approaches and presents an analysis of biometric images under various environmental conditions. This book is sure to catch the attention of scholars, researchers, practitioners, and technology aspirants who are willing to research in the field of AI and biometric security.
| Author | : Bir Bhanu |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 268 |
| Release | : 2010-11-05 |
| Genre | : Computers |
| ISBN | : 0857291246 |
Download Human Recognition at a Distance in Video Book in PDF, ePub and Kindle
Most biometric systems employed for human recognition require physical contact with, or close proximity to, a cooperative subject. Far more challenging is the ability to reliably recognize individuals at a distance, when viewed from an arbitrary angle under real-world environmental conditions. Gait and face data are the two biometrics that can be most easily captured from a distance using a video camera. This comprehensive and logically organized text/reference addresses the fundamental problems associated with gait and face-based human recognition, from color and infrared video data that are acquired from a distance. It examines both model-free and model-based approaches to gait-based human recognition, including newly developed techniques where the both the model and the data (obtained from multiple cameras) are in 3D. In addition, the work considers new video-based techniques for face profile recognition, and for the super-resolution of facial imagery obtained at different angles. Finally, the book investigates integrated systems that detect and fuse both gait and face biometrics from video data. Topics and features: discusses a framework for human gait analysis based on Gait Energy Image, a spatio-temporal gait representation; evaluates the discriminating power of model-based gait features using Bayesian statistical analysis; examines methods for human recognition using 3D gait biometrics, and for moving-human detection using both color and thermal image sequences; describes approaches for the integration face profile and gait biometrics, and for super-resolution of frontal and side-view face images; introduces an objective non-reference quality evaluation algorithm for super-resolved images; presents performance comparisons between different biometrics and different fusion methods for integrating gait and super-resolved face from video. This unique and authoritative text is an invaluable resource for researchers and graduate students of computer vision, pattern recognition and biometrics. The book will also be of great interest to professional engineers of biometric systems.
| Author | : Massimo Tistarelli |
| Publisher | : Springer |
| Total Pages | : 166 |
| Release | : 2005-05-13 |
| Genre | : Computers |
| ISBN | : 3540286381 |
Download Advanced Studies in Biometrics Book in PDF, ePub and Kindle
Automatic person authentication, the identification and verification of an individual as such, has increasingly been acknowledged as a significant aspect of various security applications. Various recognition and identification systems have been based on biometrics utilizing biometric features such as fingerprint, face, retina scans, iris patterns, hand geometry, DNA traces, gait, and others. This book originates from an international summer school on biometrics, held in Alghero, Italy, in June 2003. The seven revised tutorial lectures by leading researchers introduce the reader to biometrics-based person authentication, fingerprint recognition, gait recognition, various aspects of face recognition and face detection, topologies for biometric recognition, and hand detection. Also included are the four best selected student papers, all dealing with face recognition.
| Author | : Mayank Vatsa |
| Publisher | : CRC Press |
| Total Pages | : 316 |
| Release | : 2018-03-05 |
| Genre | : Computers |
| ISBN | : 1351264990 |
Download Deep Learning in Biometrics Book in PDF, ePub and Kindle
Deep Learning is now synonymous with applied machine learning. Many technology giants (e.g. Google, Microsoft, Apple, IBM) as well as start-ups are focusing on deep learning-based techniques for data analytics and artificial intelligence. This technology applies quite strongly to biometrics. This book covers topics in deep learning, namely convolutional neural networks, deep belief network and stacked autoencoders. The focus is also on the application of these techniques to various biometric modalities: face, iris, palmprint, and fingerprints, while examining the future trends in deep learning and biometric research. Contains chapters written by authors who are leading researchers in biometrics. Presents a comprehensive overview on the internal mechanisms of deep learning. Discusses the latest developments in biometric research. Examines future trends in deep learning and biometric research. Provides extensive references at the end of each chapter to enhance further study.
| Author | : Nelson Hebert Minaya (Graduate student) |
| Publisher | : |
| Total Pages | : 47 |
| Release | : 2021 |
| Genre | : Biometric identification |
| ISBN | : |
Download Interpretable Deep Learning-based Approach for the Gait Recognition Book in PDF, ePub and Kindle
Abstract: Human gait is a unique behavioral characteristic that can be used to recognize individuals. In recent years, the capture of gait information has become a common practice due to the advancement and accessibility of wearable devices that allow to collect it as continuous time-series. Recognizing people by processing this type of gait data has become a topic of research that looks for methods with enough high accuracy that would enable the use of gait for biometric identification. This work addresses the problem of user identification and recognition from collected multi-modal time-series gait information. The recognition problem has two different settings: the first one is closed-set recognition, whereby all testing classes are known at the time of training, and the other one is open-set recognition where unknown classes that were not in the training phase can emerge during testing. This work addresses both settings by proposing frameworks for each one. The inputs for the proposed frameworks are unit steps obtained by segmenting the multi-modal time series collected from individuals wearing a smart insole device.
| Author | : Aboul Ella Hassanien |
| Publisher | : Springer Nature |
| Total Pages | : 737 |
| Release | : 2020-05-25 |
| Genre | : Technology & Engineering |
| ISBN | : 9811533830 |
Download Advanced Machine Learning Technologies and Applications Book in PDF, ePub and Kindle
This book presents the refereed proceedings of the 5th International Conference on Advanced Machine Learning Technologies and Applications (AMLTA 2020), held at Manipal University Jaipur, India, on February 13 – 15, 2020, and organized in collaboration with the Scientific Research Group in Egypt (SRGE). The papers cover current research in machine learning, big data, Internet of Things, biomedical engineering, fuzzy logic and security, as well as intelligence swarms and optimization.
| Author | : Maria De Marsico |
| Publisher | : Academic Press |
| Total Pages | : 248 |
| Release | : 2017-01-09 |
| Genre | : Technology & Engineering |
| ISBN | : 0081007124 |
Download Human Recognition in Unconstrained Environments Book in PDF, ePub and Kindle
This book provides a unique picture of the complete ‘in-the-wild’ biometric recognition processing chain; from data acquisition through to detection, segmentation, encoding, and matching reactions against security incidents. Coverage includes: Data hardware architecture fundamentals Background subtraction of humans in outdoor scenes Camera synchronization Biometric traits: Real-time detection and data segmentation Biometric traits: Feature encoding / matching Fusion at different levels Reaction against security incidents Ethical issues in non-cooperative biometric recognition in public spaces With this book readers will learn how to: Use computer vision, pattern recognition and machine learning methods for biometric recognition in real-world, real-time settings, especially those related to forensics and security Choose the most suited biometric traits and recognition methods for uncontrolled settings Evaluate the performance of a biometric system on real world data Presents a complete picture of the biometric recognition processing chain, ranging from data acquisition to the reaction procedures against security incidents Provides specific requirements and issues behind each typical phase of the development of a robust biometric recognition system Includes a contextualization of the ethical/privacy issues behind the development of a covert recognition system which can be used for forensics and security activities
