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Object Recognition with Discriminately Trained Part-Based Model on HOG (Histogram of Oriented Gradients)

  • Thanikonda Alekhya
  • S. Ranjan Mishra
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 381)

Abstract

The object recognization techniques which are available at present cannot process the partial visible objects and cannot classify them depending on the shape. This is the main objective of my proposed system which is to recognize the object from the image if any parts of the object are visible using discriminative part-based model .The main objectives of this work was to apply the coarse root filter method and get the high-resolution parts that are converted into deformable models and are stored in training dataset. An object can be identified by matching with deformable cost of the object model present in the training dataset.

Keywords

Object detection Coarse root filter Deformable model HOG (Histogram of oriented Gradients) 

References

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Copyright information

© Springer India 2016

Authors and Affiliations

  1. 1.Anil Neerukonda Institute of Technology and SciencesVisakhapatnamIndia

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