04815nam a22004335i 4500001001800000003000900018005001700027007001500044008004100059020001800100020001900118024003500137082001400172082001500186100002500201245009300226264005900319300003400378336002600412337002600438338003600464347002400500490004800524505088100572520247501453650002203928650002103950650003303971650002204004650004204026650002504068650002704093700002204120710003404142773002004176776003604196830004804232856010104280978-0-85729-124-0DE-He21320260521092036.0cr nn 008mamaa101109s2010    xxk|    s    |||| 0|eng d  a9780857291240  a997808572912407 a10.1007/978-0-85729-124-02doi04a006.622304a006.372231 aBhanu, Bir.eauthor.10aHuman Recognition at a Distance in Videoh[electronic resource] /cby Bir Bhanu, Ju Han. 1aLondon :bSpringer London :bImprint: Springer,c2010.  aXXV, 253 p.bonline resource.  atextbtxt2rdacontent  acomputerbc2rdamedia  aonline resourcebcr2rdacarrier  atext filebPDF2rda1 aAdvances in Pattern Recognition,x2191-65860 ato Gait-Based Individual Recognition at a Distance -- Gait-Based Individual Recognition at a Distance -- Gait Representations in Video -- Model-Free Gait-Based Human Recognition in Video -- Discrimination Analysis for Model-Based Gait Recognition -- Model-Based Human Recognition-2D and 3D Gait -- Fusion of Color/Infrared Video for Human Detection -- Face Recognition at a Distance in Video -- Super-Resolution of Facial Images in Video at a Distance -- Evaluating Quality of Super-Resolved Face Images -- Integrated Face and Gait for Human Recognition at a Distance in Video -- Integrating Face Profile and Gait at a Distance -- Match Score Level Fusion of Face and Gait at a Distance -- Feature Level Fusion of Face and Gait at a Distance -- Conclusions for Integrated Gait and Face for Human Recognition at a Distance in Video -- Conclusions and Future Work.  aMost 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 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 of 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. Dr. Bir Bhanu is Distinguished Professor of Electrical Engineering, and Director of the Center for Research in Intelligent Systems, at the University of California, Riverside, USA. Dr. Ju Han is a Specialist at the Energy Biosciences Institute, a joint appointment with the Lawrence Berkeley National Laboratory and the University of California, Berkeley, USA. 0aCOMPUTER SCIENCE. 0aCOMPUTER VISION. 0aOPTICAL PATTERN RECOGNITION.14aCOMPUTER SCIENCE.24aIMAGE PROCESSING AND COMPUTER VISION.24aPATTERN RECOGNITION.24aCOMPUTERS AND SOCIETY.1 aHan, Ju.eauthor.2 aSpringerLink (Online service)0 tSpringer eBooks08iPrinted edition:z9780857291233 0aAdvances in Pattern Recognition,x2191-658640uhttp://dx.doi.org/10.1007/978-0-85729-124-0zVer el texto completo en las instalaciones del CICY