A study on depth map generation using a light field camera and a monocular RGB camera based on deep learning

2019 ◽  
Author(s):  
Makoto Takamatsu ◽  
Makoto Hasegawa
Keyword(s):  
Deep Learning ◽  
Light Field ◽  
Depth Map ◽  
Map Generation

scholarly journals Light Field Image Quality Enhancement by a Lightweight Deformable Deep Learning Framework for Intelligent Transportation Systems

Electronics ◽  
2021 ◽  
Vol 10 (10) ◽  
pp. 1136
Author(s):  
David Augusto Ribeiro ◽  
Juan Casavílca Silva ◽  
Renata Lopes Rosa ◽  
Muhammad Saadi ◽  
Shahid Mumtaz ◽  
...  
Keyword(s):  
Deep Learning ◽  
Image Quality ◽  
Intelligent Transportation Systems ◽  
Light Field ◽  
State Of The Art ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Machine Learning Algorithms ◽  
Learning Framework ◽  
Reconstruction Methods

Light field (LF) imaging has multi-view properties that help to create many applications that include auto-refocusing, depth estimation and 3D reconstruction of images, which are required particularly for intelligent transportation systems (ITSs). However, cameras can present a limited angular resolution, becoming a bottleneck in vision applications. Thus, there is a challenge to incorporate angular data due to disparities in the LF images. In recent years, different machine learning algorithms have been applied to both image processing and ITS research areas for different purposes. In this work, a Lightweight Deformable Deep Learning Framework is implemented, in which the problem of disparity into LF images is treated. To this end, an angular alignment module and a soft activation function into the Convolutional Neural Network (CNN) are implemented. For performance assessment, the proposed solution is compared with recent state-of-the-art methods using different LF datasets, each one with specific characteristics. Experimental results demonstrated that the proposed solution achieved a better performance than the other methods. The image quality results obtained outperform state-of-the-art LF image reconstruction methods. Furthermore, our model presents a lower computational complexity, decreasing the execution time.

Deep-learning-enhanced light-field microscopy

2021 ◽  
Vol 18 (5) ◽  
pp. 459-460
Author(s):  
Kai Wang
Keyword(s):  
Deep Learning ◽  
Light Field

Low complexity 3D depth map generation for stereo applications

2011 ◽  
Author(s):  
Cheng-An Chien ◽  
Cheng-Yen Chang ◽  
Jui-Sheng Lee ◽  
Jia-Hou Chang ◽  
Jiun-In Guo
Keyword(s):  
Depth Map ◽  
Low Complexity ◽  
Map Generation
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