Nowadays, I research about the Pose estimation and OpenCV for the new projects. I found the good articles on this topic so that I want to share with you;
Firstly, I mentioned about the VNECT: Real-time 3D Human Pose Estimation with Single RGB camera;
We present the first real-time method to capture the full global 3D skeletal pose of a human in a stable, temporally consistent manner using a single RGB camera. Our method combines a new convolutional neural network (CNN) based pose regressor with kinematic skeleton fitting. Our novel fully-convolutional pose formulation regresses 2D and 3D joint positions jointly in real time and does not require tightly cropped input frames. A real-time kinematic skeleton fitting method uses the CNN output to yield temporally stable 3D global pose reconstructions on the basis of a coherent kinematic skeleton. This makes our approach the first monocular RGB method usable in real-time applications such as 3D character control—thus far, the only monocular methods for such applications employed specialized RGB-D cameras. Our method’s accuracy is quantitatively on par with the best offline 3D monocular RGB pose estimation methods. Our results are qualitatively comparable to, and sometimes better than, results from monocular RGB-D approaches, such as the Kinect. However, we show that our approach is more broadly applicable than RGB-D solutions, i.e., it works for outdoor scenes, community videos, and low quality commodity RGB cameras.
Secondly, I found another human body pose estimation paper also this have github repo and I would be tried on my computer. Paper name is Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields and you can find article in here, this paper use 2D pose estimation. And you can find the repo here.
I tried second paper’s code on my computer and it works fine. You can easily install with following commands which are explained on repo.