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ShapeIndex based Applications of Local Features for Object Recognition - Tapa blanda

 
9783659885839: ShapeIndex based Applications of Local Features for Object Recognition

Sinopsis

Humans make object recognition look trivial. We can easily identify objects in our surroundings, regardless of their circumstances, whether they are upside down, different of colour or texture, partly occluded, etc. Even objects that appear in many different forms, like vases, or objects that are subject to considerable shape deviations, such as trees, can easily be generalized by our brain to one kind of object. Objet identification is done by integrating scale invariant feature extraction (SIFT) and shape index representation of range images allows matching of surface with different scales and orientations. Shape index is obtained and which is used as a local descriptor or key-point descriptor. Key-point descriptors are identified where shape index values are extremum. So, proposed project is for object identification uses 2 different properties like 3D surface properties for shape index identification and 2D scale invariant feature transform for key-point detection and feature extraction. This proposed method may be applicable for scaled, rotated and occluded range images.

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Reseña del editor

Humans make object recognition look trivial. We can easily identify objects in our surroundings, regardless of their circumstances, whether they are upside down, different of colour or texture, partly occluded, etc. Even objects that appear in many different forms, like vases, or objects that are subject to considerable shape deviations, such as trees, can easily be generalized by our brain to one kind of object. Objet identification is done by integrating scale invariant feature extraction (SIFT) and shape index representation of range images allows matching of surface with different scales and orientations. Shape index is obtained and which is used as a local descriptor or key-point descriptor. Key-point descriptors are identified where shape index values are extremum. So, proposed project is for object identification uses 2 different properties like 3D surface properties for shape index identification and 2D scale invariant feature transform for key-point detection and feature extraction. This proposed method may be applicable for scaled, rotated and occluded range images.

Biografía del autor

Kishore Kumar D received his M.S in Software Engg from VIT University Vellore in the year 2015. He has done many projects. He is working in Cognizant Tech. Sols. Second Author, Chiranji Lal Chowdhary obtained his B.E. & M.Tech. in CSE. He has more than 10 years of experience in teaching and research. He is working at VIT University Vellore INDIA.

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  • EditorialLAP LAMBERT Academic Publishing
  • Año de publicación2016
  • ISBN 10 3659885835
  • ISBN 13 9783659885839
  • EncuadernaciónTapa blanda
  • IdiomaInglés
  • Número de páginas68
  • Contacto del fabricanteno disponible

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D. Kishore Kumar
ISBN 10: 3659885835 ISBN 13: 9783659885839
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Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Humans make object recognition look trivial. We can easily identify objects in our surroundings, regardless of their circumstances, whether they are upside down, different of colour or texture, partly occluded, etc. Even objects that appear in many different forms, like vases, or objects that are subject to considerable shape deviations, such as trees, can easily be generalized by our brain to one kind of object. Objet identification is done by integrating scale invariant feature extraction (SIFT) and shape index representation of range images allows matching of surface with different scales and orientations. Shape index is obtained and which is used as a local descriptor or key-point descriptor. Key-point descriptors are identified where shape index values are extremum. So, proposed project is for object identification uses 2 different properties like 3D surface properties for shape index identification and 2D scale invariant feature transform for key-point detection and feature extraction. This proposed method may be applicable for scaled, rotated and occluded range images. 68 pp. Englisch. Nº de ref. del artículo: 9783659885839

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D. Kishore Kumar
Publicado por LAP LAMBERT Academic Publishing, 2016
ISBN 10: 3659885835 ISBN 13: 9783659885839
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Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Humans make object recognition look trivial. We can easily identify objects in our surroundings, regardless of their circumstances, whether they are upside down, different of colour or texture, partly occluded, etc. Even objects that appear in many different forms, like vases, or objects that are subject to considerable shape deviations, such as trees, can easily be generalized by our brain to one kind of object. Objet identification is done by integrating scale invariant feature extraction (SIFT) and shape index representation of range images allows matching of surface with different scales and orientations. Shape index is obtained and which is used as a local descriptor or key-point descriptor. Key-point descriptors are identified where shape index values are extremum. So, proposed project is for object identification uses 2 different properties like 3D surface properties for shape index identification and 2D scale invariant feature transform for key-point detection and feature extraction. This proposed method may be applicable for scaled, rotated and occluded range images. Nº de ref. del artículo: 9783659885839

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D. Kishore Kumar|Chiranji Lal Chowdhary
Publicado por LAP LAMBERT Academic Publishing, 2016
ISBN 10: 3659885835 ISBN 13: 9783659885839
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Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Kishore Kumar D.Kishore Kumar D received his M.S in Software Engg from VIT University Vellore in the year 2015. He has done many projects. He is working in Cognizant Tech. Sols. Second Author, Chiranji Lal Chowdhary obtained his B.E. Nº de ref. del artículo: 158248632

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Taschenbuch. Condición: Neu. Neuware -Humans make object recognition look trivial. We can easily identify objects in our surroundings, regardless of their circumstances, whether they are upside down, different of colour or texture, partly occluded, etc. Even objects that appear in many different forms, like vases, or objects that are subject to considerable shape deviations, such as trees, can easily be generalized by our brain to one kind of object. Objet identification is done by integrating scale invariant feature extraction (SIFT) and shape index representation of range images allows matching of surface with different scales and orientations. Shape index is obtained and which is used as a local descriptor or key-point descriptor. Key-point descriptors are identified where shape index values are extremum. So, proposed project is for object identification uses 2 different properties like 3D surface properties for shape index identification and 2D scale invariant feature transform for key-point detection and feature extraction. This proposed method may be applicable for scaled, rotated and occluded range images.Books on Demand GmbH, Überseering 33, 22297 Hamburg 68 pp. Englisch. Nº de ref. del artículo: 9783659885839

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D. Kishore Kumar
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Paperback. Condición: Brand New. 68 pages. 8.66x5.91x0.16 inches. In Stock. Nº de ref. del artículo: 3659885835

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Kishore Kumar, D., Chowdhary, Chiranji Lal
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