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The application of deep learning on depth from multi-array camera

Javidnia, Hossein
; 
Bazrafkan, Shabab
; 
Corcoran, Peter
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Identifiers
http://hdl.handle.net/10379/16682
 https://doi.org/10.13025/18644
Publication Date
2018-01-02
Keywords
Cameras, Estimation, Neural networks, Three-dimensional displays, Computer vision
Type
Conference Paper
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Citation
Javidnia, Hossein, Bazrafkan, Shabab, & Corcoran, Peter. (2018). The application of deep learning on depth from multi-array camera. Paper presented at the 2018 IEEE International Conference on Consumer Electronics (ICCE), Las Vegas, NV, USA, 02-14 January.
Abstract
Consumer-level multi-array cameras are a key enabling technology for next generation smartphones imaging systems. The present paper aims to analyze the accuracy of the depth estimation while using different camera combinations in a multi-array camera. This is done by providing a framework of deep neural networks to determine depth map from a sequence of images captured by a multi-array camera. Capturing depth information enables users to perform a range of post-capture edits such as refocusing, and creating a 3D model of any scene. Thus it is essential to calculate an accurate depth map while using the minimum computational resources.
Funder
Science Foundation Ireland
FotoNation Ltd
Publisher
Institute of Electrical and Electronics Engineers
Publisher DOI
Rights
Attribution-NonCommercial-NoDerivs 3.0 Ireland
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Electrical and Electronic Engineering (Conference Papers)