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3D Object Classification Using HOG3D

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Proceedings of International Conference on Data Science and Applications

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 287))

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Abstract

A crucial component of artificial intelligence and image processing is 3D object classification. It helps to achieve significant and complex changes in performance through feature representation and processing of the images. Feature extraction plays a significant step in machine learning as it facilitates the feeding of insightful and non-redundant values to the machine learning algorithms. In this paper, we will present a framework to construct a 3D object classification system using several machine learning classifiers, and features were extracted using a local object structure descriptor called the 3D Voxel histogram of oriented gradient. We say that incorporating 3D classification tasks is a powerful strategy. This means enhancing performance, precision, and efficiency of learning. The system contributed to increase efficiency and produced impressive results of 88 and 89% accuracy using Support vector machine and extreme Gradient Boosting, respectively. The results will be discussed and evaluated.

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Authors and Affiliations

  1. Department of Cybernetics and Artificial intelligence, Technical University of Kosice, Kosice, Slovak Republic

    Fouzia Adjailia, Andrinandrasana David Rasamoelina & Peter Sincak

Authors
  1. Fouzia Adjailia
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  2. Andrinandrasana David Rasamoelina
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  3. Peter Sincak
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Corresponding author

Correspondence to Fouzia Adjailia .

Editor information

Editors and Affiliations

  1. Computer Science & Engineering and Information Technology, Jaypee Institute of Information Technology, Noida, Uttar Pradesh, India

    Mukesh Saraswat

  2. Department of Computer Science and Engineering, Jadavpur University, Kolkata, West Bengal, India

    Sarbani Roy

  3. Department of Computer Science and Engineering, Jadavpur University, Kolkata, West Bengal, India

    Chandreyee Chowdhury

  4. Faculty of Engineering and Information Technology, University of Technology Sydney, Ultimo, NSW, Australia

    Amir H. Gandomi

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Adjailia, F., Rasamoelina, A.D., Sincak, P. (2022). 3D Object Classification Using HOG3D. In: Saraswat, M., Roy, S., Chowdhury, C., Gandomi, A.H. (eds) Proceedings of International Conference on Data Science and Applications. Lecture Notes in Networks and Systems, vol 287. Springer, Singapore. https://doi.org/10.1007/978-981-16-5348-3_36

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