Inspiration
Our inspiration is helping the 113 Nigerian schoolgirls from Chibok (and their families) who were kidnapped by Boko Haram in 2014 that are still missing. Our goal was to create an app that would let you take a photo of someone and determine if they were one of those girls. In addition to this, the National Center for Missing and Exploited Children has over 4,000 children in their database as of today. You can apply visual recognition technology to a database like the NCMEC or FBI Missing so that when you take a photo of someone you can identify whether or not they're in the database.
What it does
an iOS app that uses IBM Watson's API for Visual Recognition and determines gender, age and whether or not they are wearing a headscarf. In the future we would like to train this API for facial aging, ethnicity, time and geolocation of where the photo was taken.
How we built it
We researched iOS app development and Dvir built an app by reading textbooks and watching youtube videos. Grace learned how to use Watson APIs and fine tuned them specific for identifying the missing girls.
Challenges we ran into
We are both freshman without much programming knowledge. Getting access to and utilizing the Watson API for Visual Recognition was very hard. Also making the database of missing girls to teach the API was time-consuming and sad because these are real people.
Accomplishments that we're proud of
We learned Swift without any prior knowledge of the language. Watson APIs are notably difficult to work with and we only had 2 people on the team.
What we learned
Swift -IBM Watson APIs
What's next for Case By Face Basis
more training for the Watson API, finishing the app and publishing on the App Store
Built With
- api
- database
- ibm-watson
- swift
- visual-recognition
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