What it does
Human Pose Estimation is defined as the problem of localization of human joints (also known as keypoints - elbows, wrists, etc) in images or videos. It is also defined as the search for a specific pose in space of all articulated poses. Human Pose Estimation has some pretty cool applications and is heavily used in Action recognition, Animation, Gaming, etc. For example, a very popular Deep Learning app HomeCourt uses Pose Estimation to analyse Basketball player movements
I leaned about
Tensorflow and opencv
What's next for Human Pose Estimation
By scaling this project bigger this would be used in detect the movement of sport mens and other players.
Conclusion
Human Pose Estimation is an evolving discipline with opportunity for research across various fronts. Recently, there has been a noticeable trend in Human Pose Estimation of moving towards the use of deep learning, specifically CNN based approaches, due to their superior performance across tasks and datasets. One of the main reason for the success of deep learning is the availability of large amounts of training data, especially with the advent of the COCO and Human3.6M datasets.
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