Using Computer Vision to Detect Ethnicity in Videos and Improve Ethnicity Awareness

The team of more than 40 AI engineers developed a Machine Learning algorithm to classify the ethnicities of people seen on TV and detect faces in videos.

The Problem

Ethnic diversity is one form of social complexity found in most contemporary societies. Ethnic self-identification and membership in an ascribed ethnic group are important because they control, limit, and/or enhance opportunities for well-being in society. Ethnicity awareness is a crucial part of Identity development and adolescent development in the time that we need racism awareness.

The Project Results 

The team developed a Machine Learning algorithm to classify the ethnicities of people seen on TV and detect faces in videos. Different task groups built multiple models and fine-tuned them using datasets collected through active learning processes that classify faces into six identities.

Source: Ceretai & Omdena

First Omdena Project?

Join the Omdena community to make a real-world impact and develop your career

Build a global network and get mentoring support

Earn money through paid gigs and access many more opportunities

Your benefits

Address a significant real-world problem with your skills

Get hired at top companies by building your Omdena project portfolio (via certificates, references, etc.)

Access paid projects, speaking gigs, and writing opportunities

Requirements

Good English

A very good grasp in computer science and/or mathematics

Student, (aspiring) data scientist, (senior) ML engineer, data engineer, or domain expert (no need for AI expertise)

Programming experience with Python

Understanding of Computer Vision and Machine Learning.

This challenge is hosted with our friends at

Application Form