Overview of 3D object detection through fog and occlusion: passive integral imaging vs active LiDAR sensing

K. Usmani; T. O'Connor; P. Wani; B. Javidi

doi:10.1117/12.3013479

7 June 2024 Overview of 3D object detection through fog and occlusion: passive integral imaging vs active LiDAR sensing

K. Usmani, T. O'Connor, P. Wani, B. Javidi

Author Affiliations +

Proceedings Volume 13041, Three-Dimensional Imaging, Visualization, and Display 2024; 1304105 (2024) https://doi.org/10.1117/12.3013479
Event: SPIE Defense + Commercial Sensing, 2024, National Harbor, Maryland, United States

Conference Poster

Abstract

This paper presents an overview of a previously published work on the performance comparison of different sensors (Visible, LWIR, and LiDAR-based imaging systems) for the task of object detection and classification in the presence of degradation such as fog and partial occlusions. Three-dimensional integral imaging has been shown to improve the detection accuracy of object detectors operating in both visible and LWIR domains. As fog affects the image quality of different sensors in different ways, we have trained deep learning detectors for each sensor for 2D imaging as well as 3D integral imaging to compare the performance of sensors in the presence of degradation such as fog and partial occlusions.

Conference Presentation

Citation Download Citation

K. Usmani, T. O'Connor, P. Wani, and B. Javidi "Overview of 3D object detection through fog and occlusion: passive integral imaging vs active LiDAR sensing", Proc. SPIE 13041, Three-Dimensional Imaging, Visualization, and Display 2024, 1304105 (7 June 2024); https://doi.org/10.1117/12.3013479

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