Skip to main content

Classification of Activities of Daily Living(ADL) using depth videos and audio

Project description


Recognition of Activities of Daily Living(ADL) with privacy protection using depth and audio data.


Making a phone call, clapping, drinking, eating, entering from door, exiting from door, falling, lying down, opening pill container, picking object, reading, sit still, sitting down, sleeping, standing up, sweeping, using laptop, using phone, wake up, walking, washing hand, watching TV, water pouring and writing


  • python >= 2.7
  • numpy
  • librosa
  • noisereduce
  • cv2
  • keras

This project is developed as a FYP, UoM, 2019.



Project details

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Files for adl-recognition, version 1.0.1
Filename, size File type Python version Upload date Hashes
Filename, size adl_recognition-1.0.1-py3-none-any.whl (110.6 MB) File type Wheel Python version py3 Upload date Hashes View
Filename, size adl_recognition-1.0.1.tar.gz (110.6 MB) File type Source Python version None Upload date Hashes View

Supported by

AWS AWS Cloud computing Datadog Datadog Monitoring DigiCert DigiCert EV certificate Facebook / Instagram Facebook / Instagram PSF Sponsor Fastly Fastly CDN Google Google Object Storage and Download Analytics Pingdom Pingdom Monitoring Salesforce Salesforce PSF Sponsor Sentry Sentry Error logging StatusPage StatusPage Status page