Presentation + Paper
1 April 2020 3D point cloud reconstruction from a single 4D light field image
Author Affiliations +
Abstract
Obtaining accurate and noise-free three-dimensional (3D) reconstructions from real world scenes has grown in importance in recent decades. In this paper, we propose a novel strategy for the reconstruction of a 3D point cloud of an object from a single 4D light field (LF) image based on the transformation of point-plane correspondences. Considering a 4D LF image as an input, we first estimate the depth map using point correspondences between sub-aperture images. We then apply histogram equalization and histogram stretching to enhance the separation between depth planes. The main aim of this step is to increase the distance between adjacent depth layers and to enhance the depth map. We then detect edge contours of the original image using fast canny edge detection, and combine linearly the result with that of the previous steps. Following this combination, by transforming the point-plane correspondence, we can obtain the 3D structure of the point cloud. The proposed method avoids feature extraction, segmentation and the extraction of occlusion masks required by other methods, and due to this, our method can reliably mitigate noise. We tested our method with synthetic and real world image databases. To verify the accuracy of our method, we compared our results with two different state-of-the-art algorithms. In this way, we used the LOD (Level of Detail) to compare the number of points needed to describe an object. The results showed that our method had the highest level of detail compared to other existing methods.
Conference Presentation
© (2020) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Helia Farhood, Stuart Perry, Eva Cheng, and Juno Kim "3D point cloud reconstruction from a single 4D light field image", Proc. SPIE 11353, Optics, Photonics and Digital Technologies for Imaging Applications VI, 1135313 (1 April 2020); https://doi.org/10.1117/12.2555292
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KEYWORDS
Clouds

3D image processing

3D image reconstruction

Cameras

3D modeling

3D image enhancement

Edge detection

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