IMAGO: A family photo album dataset for a socio-historical analysis of the twentieth century
This work provides a new digital dataset and a deep learning methodology to enable socio-historical analysis of family photo albums for historians and social-cultural anthropologists, addressing the challenge of scattered physical collections.
The IMAGO dataset, comprising family photo albums from 1845 to 2009, was analyzed using a deep learning approach to assess image dates and socio-historical contexts without external information. This analysis demonstrated merit for socio-historical research.
Although one of the most popular practices in photography since the end of the 19th century, an increase in scholarly interest in family photo albums dates back to the early 1980s. Such collections of photos may reveal sociological and historical insights regarding specific cultures and times. They are, however, in most cases scattered among private homes and only available on paper or photographic film, thus making their analysis by academics such as historians, social-cultural anthropologists and cultural theorists very cumbersome. In this paper, we analyze the IMAGO dataset including photos belonging to family albums assembled at the University of Bologna's Rimini campus since 2004. Following a deep learning-based approach, the IMAGO dataset has offered the opportunity of experimenting with photos taken between year 1845 and year 2009, with the goals of assessing the dates and the socio-historical contexts of the images, without use of any other sources of information. Exceeding our initial expectations, such analysis has revealed its merit not only in terms of the performance of the approach adopted in this work, but also in terms of the foreseeable implications and use for the benefit of socio-historical research. To the best of our knowledge, this is the first work that moves along this path in literature.