Recognising people in videos using a pre-trained deep learning model

  • R0
  • Day 2, 16:30‑17:15
  • English talk
  • Data Analysis
  • Intermediate

In this talk, I will present how to recognise speakers and their speaking sessions in a filmed meeting using deep learning (deep convolutional neural networks; CNN). This project uses the "transfer learning" approach. Pre-trained CNN models, such as the VGG face descriptor used in this project, enable everyone to analyse photos or videos without training his own CNN. I will explain how to use a pre-trained model to extract face features and use clustering methods to identify different people without knowing their identity in advance. Results of a real case will be shown. Application and restriction of this method will be discussed.

Talk Detail

Project page and Github repository: * Website: * Github: </br> Packages used in this project: - opencv for video reading and image pre-processing - caffe for running CNN models - pre-trained VGG face desciptor - sklearn for clustering

Speaker Information

Chia-Chun Lu

Chia-Chun is a scientist and pianist. She is interested in various areas including astrophysics, data science, software engineering, and music. She currently works as an algorithm engineer at OnePlus.