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المؤلفRegaya, Yousra
المؤلفFadli, Fodil
المؤلفAmira, Abbes
تاريخ الإتاحة2024-03-18T09:56:15Z
تاريخ النشر2019-10
اسم المنشورISSE 2019 - 5th IEEE International Symposium on Systems Engineering, Proceedings
المعرّفhttp://dx.doi.org/10.1109/ISSE46696.2019.8984428
الاقتباسRegaya, Y., Fadli, F., & Amira, A. (2019, October). 3d point cloud enhancement using unsupervised anomaly detection. In 2019 International Symposium on Systems Engineering (ISSE) (pp. 1-6). IEEE.
الترقيم الدولي الموحد للكتاب 978-172811783-6
معرّف المصادر الموحدhttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85081084507&origin=inward
معرّف المصادر الموحدhttp://hdl.handle.net/10576/53152
الملخص3D point cloud is increasingly getting attention for perceiving 3D environment which is needed in many emerging applications. This data structure is challenging due to its characteristics and the limitation of the acquisition step which adds a considerable amount of noise. Therefore, enhancing 3D point clouds is a very crucial and critical step. In this paper, we investigate two promising unsupervised techniques which are One-Class SVM (OCSVM) and Isolation Forest (IF). These two techniques optimize the separation between relevant/normal points and irrelevant/noisy points. For evaluation, three metrics are computed, which are the processing time, the number of detected noisy points, and Peak Signal-to-Noise (PSNR) in order to compare the both proposed techniques with one of the recommended filters in the literature which is Moving Least Square (MLS) filter. The obtained results reveal promising capability in terms of effectiveness. However, OCSVM technique suffers from high computational time; therefore, its efficiency is enhanced using modern Graphics Processing Unit (GPU) with an average rate improvement of 1.8.
اللغةen
الناشرInstitute of Electrical and Electronics Engineers Inc. (IEEE)
الموضوعAnomaly Detection
Denoising
Isolation Forest
One-Class SVM
Point Cloud
Unsupervised
العنوان3D point cloud enhancement using unsupervised anomaly detection
النوعConference Paper
الصفحات1-6
dc.accessType Full Text


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