Synopsis
The automatic person re-identification problem resides in matching an unknown person image to a database of previously labeled images of people. Comparison among two image features is commonly accomplished by distance metrics. Although features and distance metrics can be handcrafted or trainable, the latter type has demonstrated more potential to breakthroughs in achieving state-of-the-art performance over public data sets. A recent paradigm that allows to work with trainable features is deep learning. In this book, we present a novel deep learning strategy, so called coarse-to-fine learning (CFL), as well as a novel type of feature - the convolutional covariance features (CCF), for person re-identification. CFL is based on the human learning process. After extracting the convolutional features via CFL, those ones are then wrapped in covariance matrices, composing the CCF. The performance of the proposed framework was assessed comparatively against 18 state-of-the-art methods by using public data sets (VIPeR, i-LIDS, CUHK01 and CUHK03), achieving superior performance.
"synopsis" may belong to another edition of this title.
About the Author
Alexandre Franco received his PhD in Mechatronics from Federal University of Bahia, Brazil, in 2016. His main research area is image pattern recognition. He has published several papers in the field of computer vision and pattern recognition.
"About this title" may belong to another edition of this title.
Search results for On deeply learning features for automatic person re-identifi...
Seller Image
On deeply learning features for automatic person re-identification
Published by
LAP LAMBERT Academic Publishing Jan 2017, 2017
ISBN 10: 3330029102
ISBN 13: 9783330029101
New
Taschenbuch
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The automatic person re-identification problem resides in matching an unknown person image to a database of previously labeled images of people. Comparison among two image features is commonly accomplished by distance metrics. Although features and distance metrics can be handcrafted or trainable, the latter type has demonstrated more potential to breakthroughs in achieving state-of-the-art performance over public data sets. A recent paradigm that allows to work with trainable features is deep learning. In this book, we present a novel deep learning strategy, so called coarse-to-fine learning (CFL), as well as a novel type of feature - the convolutional covariance features (CCF), for person re-identification. CFL is based on the human learning process. After extracting the convolutional features via CFL, those ones are then wrapped in covariance matrices, composing the CCF. The performance of the proposed framework was assessed comparatively against 18 state-of-the-art methods by using public data sets (VIPeR, i-LIDS, CUHK01 and CUHK03), achieving superior performance. 112 pp. Englisch. Seller Inventory # 9783330029101
Seller Image
On deeply learning features for automatic person re-identification
Published by
LAP LAMBERT Academic Publishing, 2017
ISBN 10: 3330029102
ISBN 13: 9783330029101
New
Softcover
Seller: moluna, Greven, Germany
Seller rating 5 out of 5 stars
Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Franco AlexandreAlexandre Franco received his PhD in Mechatronics from Federal University of Bahia, Brazil, in 2016. His main research area is image pattern recognition. He has published several papers in the field of computer vision. Seller Inventory # 158122913
Buy New
£ 36.62
£ 41.76 shipping
Ships from Germany to U.S.A.
Ships from Germany to U.S.A.
Quantity: Over 20 available
Stock Image
On deeply learning features for automatic person re-identification
Published by
LAP LAMBERT Academic Publishing, 2017
ISBN 10: 3330029102
ISBN 13: 9783330029101
New
Paperback
Seller: Revaluation Books, Exeter, United Kingdom
Seller rating 5 out of 5 stars
Paperback. Condition: Brand New. 112 pages. 8.66x5.91x0.26 inches. In Stock. Seller Inventory # 3330029102
Buy New
£ 70.09
£ 10 shipping
Ships from United Kingdom to U.S.A.
Ships from United Kingdom to U.S.A.
Quantity: 1 available
Seller Image
On deeply learning features for automatic person re-identification
Published by
LAP LAMBERT Academic Publishing Jan 2017, 2017
ISBN 10: 3330029102
ISBN 13: 9783330029101
New
Taschenbuch
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -The automatic person re-identification problem resides in matching an unknown person image to a database of previously labeled images of people. Comparison among two image features is commonly accomplished by distance metrics. Although features and distance metrics can be handcrafted or trainable, the latter type has demonstrated more potential to breakthroughs in achieving state-of-the-art performance over public data sets. A recent paradigm that allows to work with trainable features is deep learning. In this book, we present a novel deep learning strategy, so called coarse-to-fine learning (CFL), as well as a novel type of feature - the convolutional covariance features (CCF), for person re-identification. CFL is based on the human learning process. After extracting the convolutional features via CFL, those ones are then wrapped in covariance matrices, composing the CCF. The performance of the proposed framework was assessed comparatively against 18 state-of-the-art methods by using public data sets (VIPeR, i-LIDS, CUHK01 and CUHK03), achieving superior performance.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 112 pp. Englisch. Seller Inventory # 9783330029101
Seller Image
On deeply learning features for automatic person re-identification
Published by
LAP LAMBERT Academic Publishing, 2017
ISBN 10: 3330029102
ISBN 13: 9783330029101
New
Taschenbuch
Seller: AHA-BUCH GmbH, Einbeck, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The automatic person re-identification problem resides in matching an unknown person image to a database of previously labeled images of people. Comparison among two image features is commonly accomplished by distance metrics. Although features and distance metrics can be handcrafted or trainable, the latter type has demonstrated more potential to breakthroughs in achieving state-of-the-art performance over public data sets. A recent paradigm that allows to work with trainable features is deep learning. In this book, we present a novel deep learning strategy, so called coarse-to-fine learning (CFL), as well as a novel type of feature - the convolutional covariance features (CCF), for person re-identification. CFL is based on the human learning process. After extracting the convolutional features via CFL, those ones are then wrapped in covariance matrices, composing the CCF. The performance of the proposed framework was assessed comparatively against 18 state-of-the-art methods by using public data sets (VIPeR, i-LIDS, CUHK01 and CUHK03), achieving superior performance. Seller Inventory # 9783330029101
Seller Image
On deeply learning features for automatic person re-identification
Published by
LAP LAMBERT Academic Publishing, 2017
ISBN 10: 3330029102
ISBN 13: 9783330029101
New
Taschenbuch
Seller: preigu, Osnabrück, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. On deeply learning features for automatic person re-identification | Alexandre Franco (u. a.) | Taschenbuch | 112 S. | Englisch | 2017 | LAP LAMBERT Academic Publishing | EAN 9783330029101 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu Print on Demand. Seller Inventory # 108335848
Stock Image
On deeply learning features for automatic person re-identification
Published by
LAP LAMBERT Academic Publishing, 2017
ISBN 10: 3330029102
ISBN 13: 9783330029101
New
paperback
Seller: Mispah books, Redhill, SURRE, United Kingdom
Seller rating 4 out of 5 stars
paperback. Condition: New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book. Seller Inventory # ERICA82933300291026