Head Pose Experiments

Exploration workspace comparing DirectMHP, 6DRepNet360, CMU Panoptic tooling, and lightweight ResNet/MobileNet head-pose approaches.

PythonPyTorchOpenCV-style computer vision utilitiesYOLO-style detection/training codeONNX export and inference pathsCMU Panoptic dataset tooling3D visualization/reprojection scripts

⚡ Dataset licensing and access constraints for AGORA, CMU Pano…⚡ Model zoo fragmentation across research repos.⚡ Different angle conventions and evaluation metrics across pr…⚡ Need to distinguish copied reference code from original inte…

Snapshot

Period: Local experiment folder present in recent workspace; no Git history detected
Source: `/Users/jose/Developer/work/sparshiq/experiments/head-pose`
Domain: Head pose estimation, computer vision research survey
Status: Exploration/reference integration

Portfolio Summary

This folder appears to be a research/evaluation workspace rather than a committed project. It collects several head-pose estimation approaches and supporting dataset tooling: DirectMHP for direct multi-person full-range head pose, 6DRepNet360 for robust 360-degree rotation estimation, CMU Panoptic utilities for 3D keypoint reprojection, and lightweight ResNet/MobileNet head-pose models with ONNX export/inference paths.

Potential Portfolio Angle

This can become a strong portfolio item if it is converted from a reference workspace into an evaluated experiment:

Define a target use case, such as driver attention, classroom analytics, rail-cab operator monitoring, or multi-person scene analysis.
Compare model families on the same clips or images.
Export one lightweight model to ONNX and benchmark CPU/GPU inference.
Build a small demo that overlays yaw/pitch/roll or 3D axes on video.
Document tradeoffs: single-person vs multi-person, full-range vs frontal, accuracy vs model size, 2D detection coupling vs 3D representation.