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Motion segmentation is an essential process for many computer vision algorithms. During the last decade, a large amount of works has been trying to tackle this challenging problem, however, performances of most of them still fall far behind human perception. In this work the motion segmentation problem is studied, analyzing and reviewing the most important and newest techniques. A classification of all these techniques into different categories according to their main principle and features is proposed, and their strengths and weaknesses are pointed out. One of the most promising technique emerged from the review, the Local Subspace Affinity, is studied in its details highlighting and commenting its critical points. Some improvements to this technique are proposed and validated with tests on synthetic and real sequences. Finally further research directions are suggested.
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Informazioni sugli autori
L. Zappella is a PhD candidate at the University of Girona (Spain). X. Lladó is lecturer at the University of Girona (Spain). J. Salvi is professor at University of Girona (Spain). Authors' research interests are in the field of image processing, computer vision, motion analysis, structure from motion and 3D reconstruction.
L. Zappella is a PhD candidate at the University of Girona (Spain). X. Lladó is lecturer at the University of Girona (Spain). J. Salvi is professor at University of Girona (Spain). Authors' research interests are in the field of image processing, computer vision, motion analysis, structure from motion and 3D reconstruction.
L. Zappella is a PhD candidate at the University of Girona (Spain). X. Lladó is lecturer at the University of Girona (Spain). J. Salvi is professor at University of Girona (Spain). Authors' research interests are in the field of image processing, computer vision, motion analysis, structure from motion and 3D reconstruction.
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Motion Segmentation From Tracked Features
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LAP LAMBERT Academic Publishing Jan 2011, 2011
ISBN 10: 3844300600
ISBN 13: 9783844300604
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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Motion segmentation is an essential process for many computer vision algorithms. During the last decade, a large amount of works has been trying to tackle this challenging problem, however, performances of most of them still fall far behind human perception. In this work the motion segmentation problem is studied, analyzing and reviewing the most important and newest techniques. A classification of all these techniques into different categories according to their main principle and features is proposed, and their strengths and weaknesses are pointed out. One of the most promising technique emerged from the review, the Local Subspace Affinity, is studied in its details highlighting and commenting its critical points. Some improvements to this technique are proposed and validated with tests on synthetic and real sequences. Finally further research directions are suggested. 60 pp. Englisch. Codice articolo 9783844300604
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Motion Segmentation From Tracked Features : An improved Local Subspace Affinity algorithm without priors
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LAP LAMBERT Academic Publishing, 2011
ISBN 10: 3844300600
ISBN 13: 9783844300604
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Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Motion segmentation is an essential process for many computer vision algorithms. During the last decade, a large amount of works has been trying to tackle this challenging problem, however, performances of most of them still fall far behind human perception. In this work the motion segmentation problem is studied, analyzing and reviewing the most important and newest techniques. A classification of all these techniques into different categories according to their main principle and features is proposed, and their strengths and weaknesses are pointed out. One of the most promising technique emerged from the review, the Local Subspace Affinity, is studied in its details highlighting and commenting its critical points. Some improvements to this technique are proposed and validated with tests on synthetic and real sequences. Finally further research directions are suggested. Codice articolo 9783844300604
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Motion Segmentation From Tracked Features
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LAP LAMBERT Academic Publishing, 2011
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ISBN 13: 9783844300604
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Motion Segmentation From Tracked Features
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LAP LAMBERT Academic Publishing Jan 2011, 2011
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ISBN 13: 9783844300604
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Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Motion segmentation is an essential process for many computer vision algorithms. During the last decade, a large amount of works has been trying to tackle this challenging problem, however, performances of most of them still fall far behind human perception. In this work the motion segmentation problem is studied, analyzing and reviewing the most important and newest techniques. A classification of all these techniques into different categories according to their main principle and features is proposed, and their strengths and weaknesses are pointed out. One of the most promising technique emerged from the review, the Local Subspace Affinity, is studied in its details highlighting and commenting its critical points. Some improvements to this technique are proposed and validated with tests on synthetic and real sequences. Finally further research directions are suggested.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 60 pp. Englisch. Codice articolo 9783844300604
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Motion Segmentation From Tracked Features | An improved Local Subspace Affinity algorithm without priors
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LAP LAMBERT Academic Publishing, 2011
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ISBN 13: 9783844300604
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Taschenbuch. Condizione: Neu. Motion Segmentation From Tracked Features | An improved Local Subspace Affinity algorithm without priors | Luca Zappella (u. a.) | Taschenbuch | 60 S. | Englisch | 2011 | LAP LAMBERT Academic Publishing | EAN 9783844300604 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. Codice articolo 107122766
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Motion Segmentation From Tracked Features: An improved Local Subspace Affinity algorithm without priors
Editore:
LAP LAMBERT Academic Publishing, 2011
ISBN 10: 3844300600
ISBN 13: 9783844300604
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