Web3D Lightweight for Sketch-Based Shape Retrieval Using SVM Learning Algorithm

ZHOU Wen, JIA Jin-yuan

ACTA ELECTRONICA SINICA ›› 2019, Vol. 47 ›› Issue (1) : 92-99.

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ACTA ELECTRONICA SINICA ›› 2019, Vol. 47 ›› Issue (1) : 92-99. DOI: 10.3969/j.issn.0372-2112.2019.01.012

Web3D Lightweight for Sketch-Based Shape Retrieval Using SVM Learning Algorithm

  • ZHOU Wen, JIA Jin-yuan
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Abstract

With the rapid development of Web3D technology,the demand to use and retrieve 3D model is becoming urgent.Especially,sketch-based shape retrieval is very important.In the paper,a framework is proposed,which includes lightweight for shape,SVM-based learning algorithm.In particular,the model is simplified and then projected into multi-views images.Besides,a SVM classifier is used to classify these images.Moreover,histogram of oriented gradient (HOG) features is extracted from the input sketch image.Furthermore,K-means algorithm is used to cluster and index these features in order to generate a features dictionary.Finally,the related experiments are conducted to verify the feasibility of the approach in open source datasets.The result shows that the proposed method is robust and superior,compared with other methods.

Key words

sketch-based shape retrieval / SVM / simplified / HOG / features dictionary

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ZHOU Wen, JIA Jin-yuan. Web3D Lightweight for Sketch-Based Shape Retrieval Using SVM Learning Algorithm[J]. Acta Electronica Sinica, 2019, 47(1): 92-99. https://doi.org/10.3969/j.issn.0372-2112.2019.01.012

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Funding

Fundamental Research Funds for the Central Universities - Key Program of Interdisciplinary Project  (Class A) (No.0200219153)
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