Appearance-based 3-D Object Recognition and Pose Estimation

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In Computer Vision,Image Processing, Artificial Intelligence and Neural Networks object recognition is one of the most successful applications of image or object analysis and understanding.The recognition system typically involves some sort of sensor,the use of a model database in which all the objects models representations are saved,and a decision-making ability.When a sensor views an object the digitized image is processed so as to represent it in the same way as the models are represented in the databases.Then a recognition algorithm tries to find the model to which the object best matches.For the view-based recognition, the representations take into account the appearance of the object. To achieve 3D Object recognition(3DOR) the pose of objects are also saved in the database.In general two 3DOR techniques. They are Geometric feature-based approach and Appearance- based approach.The geometric feature-based approach uses properties of shape of object i.e. lines, curves,and vertices for object recognition descriptions.But appearance-based 3DOR is the combined effects of objects shape, reflectance properties,pose and the illumination.

Autorentext

Chiranji Lal Chowdhary received the B.E. in Computer Science & Engg. from M.B.M.Engg. College, JNV University,Jodhpur, and the M.Tech. in Computer Science & Engg. from M.S.Ramaiah Institute of Technology,Bangalore(VTU,Belgaum,IN). Presently he is working as faculty member at VIT University,Vellore,IN. Here he is also pursuing part-time PhD.

Weitere Informationen

  • Allgemeine Informationen
    • GTIN 09783843391153
    • Sprache Englisch
    • Genre Maschinenbau
    • Anzahl Seiten 76
    • Größe H220mm x B150mm x T5mm
    • Jahr 2011
    • EAN 9783843391153
    • Format Kartonierter Einband
    • ISBN 3843391157
    • Veröffentlichung 04.01.2011
    • Titel Appearance-based 3-D Object Recognition and Pose Estimation
    • Autor Chiranji Lal Chowdhary
    • Untertitel Using PCA, ICA and SVD-PCA Techniques
    • Gewicht 131g
    • Herausgeber LAP LAMBERT Academic Publishing

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