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ShapeIndex based Applications of Local Features for Object Recognition - Couverture souple

 
9783659885839: ShapeIndex based Applications of Local Features for Object Recognition

Synopsis

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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Présentation de l'éditeur

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.

Biographie de l'auteur

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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  • ÉditeurLAP LAMBERT Academic Publishing
  • Date d'édition2016
  • ISBN 10 3659885835
  • ISBN 13 9783659885839
  • ReliureBroché
  • Langueanglais
  • Nombre de pages68
  • Coordonnées du fabricantnon disponible

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Etat : 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. N° de réf. du vendeur 158248632

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Taschenbuch. Etat : 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. N° de réf. du vendeur 9783659885839

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Taschenbuch. Etat : 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. N° de réf. du vendeur 9783659885839

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Taschenbuch. Etat : 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. N° de réf. du vendeur 9783659885839

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