Point Cloud Novelty Detection Based on Latent Representations of a General Feature Extractor

Shizuka Akahori*, Satoshi Iizuka, Ken Mawatari, Kazuhiro Fukui

*この研究の対応する著者

研究成果: Conference contribution

1 被引用数 (Scopus)

抄録

We propose an effective unsupervised 3D point cloud novelty detection approach, leveraging a general point cloud feature extractor and a one-class classifier. The general feature extractor consists of a graph-based autoencoder and is trained once on a point cloud dataset such as a mathematically generated fractal 3D point cloud dataset that is independent of normal/abnormal categories. The input point clouds are first converted into latent vectors by the general feature extractor, and then one-class classification is performed on the latent vectors. Compared to existing methods measuring the reconstruction error in 3D coordinate space, our approach utilizes latent representations where the shape information is condensed, which allows more direct and effective novelty detection. We confirm that our general feature extractor can extract shape features of unseen categories, eliminating the need for autoencoder re-training and reducing the computational burden. We validate the performance of our method through experiments on several subsets of the ShapeNet dataset and demonstrate that our latent-based approach outperforms the existing methods.

本文言語English
ホスト出版物のタイトルImage and Video Technology - 11th Pacific-Rim Symposium, PSIVT 2023, Proceedings
編集者Wei Qi Yan, Minh Nguyen, Parma Nand, Xuejun Li
出版社Springer Science and Business Media Deutschland GmbH
ページ182-196
ページ数15
ISBN(印刷版)9789819703753
DOI
出版ステータスPublished - 2024
外部発表はい
イベント11th Pacific-Rim Symposium on Image and Video Technology, PSIVT 2023 - Auckland, New Zealand
継続期間: 2023 11月 222023 11月 24

出版物シリーズ

名前Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
14403 LNCS
ISSN(印刷版)0302-9743
ISSN(電子版)1611-3349

Conference

Conference11th Pacific-Rim Symposium on Image and Video Technology, PSIVT 2023
国/地域New Zealand
CityAuckland
Period23/11/2223/11/24

ASJC Scopus subject areas

  • 理論的コンピュータサイエンス
  • コンピュータサイエンス一般

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