The application of deep learning on depth from multi-array camera
Date
2018-01-02Author
Javidnia, Hossein
Bazrafkan, Shabab
Corcoran, Peter
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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.
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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.