dulocian/pose-classification

🎓 This repository holds my masters dissertation project submitted in 2023 at the North-West University (South Africa) titled 'Novel Data Augmentation Schemes for Pose Classification Using a Convolutional Neural Network'. # Pose classification 🎓 This repository holds my masters dissertation project submitted in 2023 at the North-West University, South Africa titled 'Novel Data Augmentation Schemes for Pose Classification Using a Convolutional Neural Network'. 📓 Link to dissertation (_to be added once link is available_) 💽 Link to Dayta NWU Repositroy --- Published research related to this project: 📘 **SATNAC 2019** Heuristic Data Augmentation for Improved Human Activity Recognition 📘 **SATNAC 2021** Colour-based encoding schemes for improved human pose recognition using a Convolutional neural network --- ## Set-up Ensure that the following prerequisites are installed: - NVIDIA GPU with CUDA support - NVIDIA CUDA Toolkit - cuDNN library - Python 3.7.3 - Keras The relevant Python libraries and dependencies can be installed using the requirements.txt ```bash pip install -r requirements.txt ``` --- ## Preliminary experiments The first set of experiments act as a proof of concept to establish the viability of augmentating pose data with colour information to improve the capacity of a CNN to perform pose classification. In these experiments, a curated image set was pre-processed by OpenPose to localise 18 body parts and joints across the captured human silhouettes. A baseline image set is generated by plotting the key points as white pixels onto a 32x32 image against a black backdrop. Six additional image sets are generated that incorporate colour, blending colours of overlapping key points, and tinting to reflect the OpenPose localisation confidence. ## Primary experiments The second set of experiments expands on the findings of the preliminary experiments which demonstrated that colour acted as a salient feature in pose classification. In these experiments, a video dataset designed for fall detection is pre-processed by OpenPose to localise the same 18 body parts and joints. The key point colour association is based on four different colour wheels which encode supplemen …