Humans of Paris 1900: Difference between revisions
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== Historical Background and Nadar's Collection == | == Historical Background and Nadar's Collection == | ||
== Implementation == | == 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 == | == Project execution plan == | ||
Revision as of 12:21, 12 December 2019
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
| 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 | |