Human Identification Recognition Using by Nayak Abhijit (5 results)
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Taschenbuch. Condition: Neu. Human Identification & Recognition Using Gait | Abhijit Nayak | Taschenbuch | 68 S. | Englisch | 2017 | LAP LAMBERT Academic Publishing | EAN 9783330346055 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.
Language: English
Published by LAP LAMBERT Academic Publishing Jul 2017, 2017
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Over the last few years, the use of automated systems and biometrics for security and surveillance applications has increased manifold. Traditional biometric signatures are not non-obtrusive - in the sense that they require the acti…ve consent and participation of the subject. This becomes a problem if surveillance and identification has to be carried out in a secret manner. As a low-cost non-obtrusive method for reliable person identification, human gait recognition provides a solution to this problem. This work employs a gait recognition process with binary silhouette-based input images and uses Hidden Markov Model (HMM) for the recognition process. The major objective has been to implement an efficient algorithm for the reliable identification of humans using their gait data. The experimental results provide a preliminary platform for satisfactory gait identification. This book should serve students in areas such as pattern recognition and image processing as an introduction to the promising field of human gait recognition and provides a framework to develop and implement more robust algorithms to be used in the real world. 68 pp. Englisch.
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Nayak AbhijitAbhijit Nayak graduated from NIT Rourkela, India in 2015 with a Masters in Communication and Signal Processing. His research interests include image processing and pattern recognition.Over…the last few years, the use.
Language: English
Published by LAP LAMBERT Academic Publishing Jul 2017, 2017
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Over the last few years, the use of automated systems and biometrics for security and surveillance applications has increased manifold. Traditional biometric signatures are not non-obtrusive - in the sense that they require the active c…onsent and participation of the subject. This becomes a problem if surveillance and identification has to be carried out in a secret manner. As a low-cost non-obtrusive method for reliable person identification, human gait recognition provides a solution to this problem. This work employs a gait recognition process with binary silhouette-based input images and uses Hidden Markov Model (HMM) for the recognition process. The major objective has been to implement an efficient algorithm for the reliable identification of humans using their gait data. The experimental results provide a preliminary platform for satisfactory gait identification. This book should serve students in areas such as pattern recognition and image processing as an introduction to the promising field of human gait recognition and provides a framework to develop and implement more robust algorithms to be used in the real world.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 68 pp. Englisch.
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Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Over the last few years, the use of automated systems and biometrics for security and surveillance applications has increased manifold. Traditional biometric signatures are not non-obtrusive - in the sense that they require the active co…nsent and participation of the subject. This becomes a problem if surveillance and identification has to be carried out in a secret manner. As a low-cost non-obtrusive method for reliable person identification, human gait recognition provides a solution to this problem. This work employs a gait recognition process with binary silhouette-based input images and uses Hidden Markov Model (HMM) for the recognition process. The major objective has been to implement an efficient algorithm for the reliable identification of humans using their gait data. The experimental results provide a preliminary platform for satisfactory gait identification. This book should serve students in areas such as pattern recognition and image processing as an introduction to the promising field of human gait recognition and provides a framework to develop and implement more robust algorithms to be used in the real world.
