Humans of Paris 1900

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Motivation

We take inspiration from the famous Instagram page, Humans of New York, which features pictures and stories of people living in current day New York. In similar fashion, our project, Humans of Paris, has the aim to be a platform to connect us to the people of 19th century Paris. Photography was still in its early stages when Nadar took up the craft in his atelier in Paris. Through the thousands of pictures taken by him and his son we can get a glimpse of who lived at the time. We explore the use of deep learning models to cluster similar faces to get an alternative, innovative view of the collection and allowing for serendipitous discovery of patterns and people. There is a story behind every person, and our interface highlights this by association people’s story with their picture.


Historical Background and Nadar's Collection

Implementation

Website Description

In more concrete terms, our project involves four core interfaces motivated by the above.

  • A home page highlighting the most known individuals
  • A page (FaceMap) that highlight similarities in differences in the faces of the people in the dataset.
  • A page to find your 19th century doppelganger, for fun and to gather interest in people the user my otherwise would never have known existed.
  • A way to search using tags, to allow users to find individuals of interest.

To each person in the pictures we associate background information crawled from wikipedia.

Project execution plan

Milestones

Weekly working plan
Timeframe Task Completion
Week 4
07.11 Understanding Gallica Query Gallica API
Query Gallica API
Week 5
14.10 Start preprocessing images
Choose suitable Wikipedia API
Week 6
21.10 Choose face recognition library
Get facial vectors
Try database design with Docker & Flask
Week 7
28.10 Remove irrelevant backgrounds of images
Extract age and gender from images
Design data model
Extract tags, names, birth and death years out of metadata
Week 8
04.11 Set up database environment
Set up mockup user-interface
Prepare midterm presentation
Week 9
11.11 Get tags, names, birth and death years in ready-to-use format
Handle Wikipedia false positives
Integrate face recognition functionalities into database
Week 10
18.11 Create draft of the website (frontend)
Create FaceMap using D3
Week 11
25.11 Integrate all functionalities
Finalize project website
Week 12
02.12 Write Project report