Historic Photo Analysis

Machine Learning Based Analysis of Finnish World War II Photographers

We demonstrate the benefits of using state-of-the-art machine learning methods in the analysis of historical photo archives. Specifically, we analyze prominent Finnish World War II photographers, who have captured high numbers of photographs in the publicly available Finnish Wartime Photograph Archive, which contains 160,000 photographs from Finnish Winter, Continuation, and Lapland Wars captures in 1939-1945. We were able to find some special characteristics for different photographers in terms of their typical photo content and framing (e.g., close-ups vs. overall shots, number of people). Furthermore, we managed to train a neural network that can successfully recognize the photographer from some of the photos, which shows that such photos are indeed characteristic for certain photographers. We further analyzed the similarities and differences between the photographers using the features extracted from the photographer classifier network. All the extracted information will help historical and societal studies over the photo archive .

Visualization of the photograph similarities using the t-SNE algorithm and sample photographs with a varying similarity

Example photographs of different framing categories and the corresponding detection results

Examples of successful and erroneous object detection results. Histograms of the photographs shown here and in the following examples have been equalized. We show here also object classes not used in our analysis (e.g. teddybear).

References

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