  In this paper, we present a novel algorithm to extract a quaternion from a
two dimensional camera frame for estimating a contained human skeletal pose.
The problem of pose estimation is usually tackled through the usage of stereo
cameras and intertial measurement units for obtaining depth and euclidean
distance for measurement of points in 3D space. However, the usage of these
devices comes with a high signal processing latency as well as a significant
monetary cost. By making use of MediaPipe, a framework for building perception
pipelines for human pose estimation, the proposed algorithm extracts a
quaternion from a 2-D frame capturing an image of a human object at a sub-fifty
millisecond latency while also being capable of deployment at edges with a
single camera frame and a generally low computational resource availability,
especially for use cases involving last-minute detection and reaction by
autonomous robots. The algorithm seeks to bypass the funding barrier and
improve accessibility for robotics researchers involved in designing control
systems.
