Paper
16 July 2021 Interest of pseudo-focused images for key-points detection in plenoptic imaging
Author Affiliations +
Proceedings Volume 11794, Fifteenth International Conference on Quality Control by Artificial Vision; 1179405 (2021) https://doi.org/10.1117/12.2588954
Event: Fifteenth International Conference on Quality Control by Artificial Vision, 2021, Tokushima, Japan
Abstract
Light-Field (LF) cameras allow the extraction not only of the intensity of light but also of the direction of light rays in the scene, hence it records much more information of the scene than a conventional camera. In this paper, we present a novel method to detect key-points in raw LF images by applying key-points detectors on Pseudo-Focused images (PFIs). The main advantage of this method is that we don’t need to use complex key-points detectors dedicated to light-field images. We illustrate the method in two use cases: the extraction of corners in a checkerboard and the key-points matching in two view raw light-field images. These key-points can be used for different applications e.g. calibration, depth estimation or visual odometry. Our experiments showed that our method preserves the accuracy of detection by re-projecting the pixels in the original raw images.
© (2021) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
M. Al Assaad, S. Bazeille, T. Laurain, A. Dieterlen, and C. Cudel "Interest of pseudo-focused images for key-points detection in plenoptic imaging", Proc. SPIE 11794, Fifteenth International Conference on Quality Control by Artificial Vision, 1179405 (16 July 2021); https://doi.org/10.1117/12.2588954
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KEYWORDS
Cameras

Convolutional neural networks

3D image processing

3D vision

Image analysis

Spatial resolution

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