Reconstructing Intensity Images From Binary Spatial Gradient Cameras

Suren Jayasuriya, Orazio Gallo, Jinwei Gu, Timo Aila, Jan Kautz; The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2017, pp. 20-26

Abstract


Binary gradient cameras extract edge and temporal information directly on the sensor, allowing for low-power, low-bandwidth, and high-dynamic-range capabilities---all critical factors for the deployment of embedded computer vision systems. However, these types of images require specialized computer vision algorithms and are not easy to interpret by a human observer. In this paper we propose to recover an intensity image from a single binary spatial gradient image with a deep auto-encoder. Extensive experimental results on both simulated and real data show the effectiveness of the proposed approach.

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[bibtex]
@InProceedings{Jayasuriya_2017_CVPR_Workshops,
author = {Jayasuriya, Suren and Gallo, Orazio and Gu, Jinwei and Aila, Timo and Kautz, Jan},
title = {Reconstructing Intensity Images From Binary Spatial Gradient Cameras},
booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
month = {July},
year = {2017}
}