- Developed an Android application that uses computer vision to estimate user emotional state from facial input and provide simple behavioral recommendations.
- Implemented an emotion classification pipeline using OpenCV and TensorFlow models to process images and detect facial expressions.
- Designed a feedback mechanism that maps detected emotional states to suggested activities (e.g., music, mindfulness, physical activity).
- Built the mobile application in Java with Firebase integration for data storage and basic user state persistence.
- Explored early concepts in human-centered AI, focusing on how machine perception can support user behavior and well-being.
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Oct 31, 2022
1 min read
Mood Tracker
Computer vision-based mobile system for emotion recognition and behavioral feedback