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Vol. 9 No. 1 (2023)
Special Issue: Proceedings of CVIS 2023

Articles

Fast, Accurate and Object Boundary-Aware Surface Normal Estimation from Depth Maps

https://doi.org/10.15353/jcvis.v9i1.10019

Published 2024-04-30

  • Saed Moradi
    • ,
  • Hadi Sepanj
    • ,
  • Alireza Memarmoghadam
    • ,
  • Denis Laurendeau
    • ,
  • Paul Fieguth

Abstract

In this paper, we introduce a fast and precise surface normal estimation technique designed explicitly for depth maps, also known as organized point clouds. Our approach formulates the surface normal estimation as a closed-form expression, effectively mitigating the impact of measurement noise through multi-directional averaging. We then streamline the multi-directional normal estimation process for efficiency. Additionally, we propose a straightforward yet powerful method to eliminate inaccurate normal estimations at depth discontinuities, making our approach object boundary-aware. Comparative analyses with established surface normal estimation algorithms reveal that our method not only excels in accuracy but also exhibits the speed required for real-time applications.
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