Camera-based detection and analysis of passenger status


Camera-based detection and analysis of passenger status

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Context

With the increasing spread of autonomous driving, passenger comfort is receiving growing attention alongside driving safety. The aim of this project is to record and evaluate the condition of passengers using camera-based sensor technology, including remote photoplethysmography (RPPG), in order to better understand and specifically improve their comfort. Through the use of computer vision and signal processing, the project investigates how contactless condition monitoring can contribute to more comfortable and user-centered autonomous mobility.

Tasks
  • Participation in test drives with test persons to collect measurement data
  • Pre-processing and evaluation of recorded sensor data
  • Support in the development of algorithms for camera-based analysis of facial data (e.g. using remote photoplethysmography (RPPG))
  • Evaluation of monitoring methods and sensor technology based on defined criteria
Prerequisites
  • Strong interest in computer vision and human-centered sensing
  • Knowledge of machine learning
  • Programming experience (e.g. Python, OpenCV...)
  • Analytical, problem solving and communication skills