Computer Science > Computer Vision and Pattern Recognition
[Submitted on 20 Aug 2015 (v1), last revised 1 Jun 2016 (this version, v3)]
Title:Seeing Behind the Camera: Identifying the Authorship of a Photograph
View PDFAbstract:We introduce the novel problem of identifying the photographer behind a photograph. To explore the feasibility of current computer vision techniques to address this problem, we created a new dataset of over 180,000 images taken by 41 well-known photographers. Using this dataset, we examined the effectiveness of a variety of features (low and high-level, including CNN features) at identifying the photographer. We also trained a new deep convolutional neural network for this task. Our results show that high-level features greatly outperform low-level features. We provide qualitative results using these learned models that give insight into our method's ability to distinguish between photographers, and allow us to draw interesting conclusions about what specific photographers shoot. We also demonstrate two applications of our method.
Submission history
From: Chris Thomas [view email][v1] Thu, 20 Aug 2015 16:45:17 UTC (4,764 KB)
[v2] Wed, 11 Nov 2015 06:38:08 UTC (9,165 KB)
[v3] Wed, 1 Jun 2016 01:09:08 UTC (22,186 KB)
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