HumanFallDetection

We augment human pose estimation (openpifpaf library) by support for multi-camera and multi-person tracking and a long short-term memory (LSTM) neural network to predict two classes: “Fall” or “No Fall”. From the poses, we extract five temporal and spatial features which are processed by an LSTM classifier.

Setup

pip install -r requirements.txt

Usage

python3 fall_detector.py

Citation

Please cite the following paper in your publications if our work has helped your research:
Multi-camera, multi-person, and real-time fall detection using long short term memory

@inproceedings{Taufeeque2021MulticameraMA,
                author = {Mohammad Taufeeque and Samad Koita and Nicolai Spicher and Thomas M. Deserno},
                title = {{Multi-camera, multi-person, and real-time fall detection using long short term memory}},
                volume = {11601},
                booktitle = {Medical Imaging 2021: Imaging Informatics for Healthcare, Research, and Applications},
                organization = {International Society for Optics and Photonics},
                publisher = {SPIE},
                pages = {35 -- 42},
                year = {2021},
                doi = {10.1117/12.2580700},
                URL = {https://doi.org/10.1117/12.2580700}
              }