Home exercises are significant in the rehabilitation process of physiotherapy patients, which lack immediate feedback as to the proper movement and therefore might humper patient treatment. In this paper we are proposing an algorithm for fast tracking of human body movements performed during physiotherapeutic exercises using a simple webcam home setup and common domestically available CPU computing resources. We use OpenPose for detecting body vertices in key frames and a novel vertex tracking algorithm between video frames, which leverages encoded video Motion Vectors (MVs). We show excellent tracking accuracy between frames and x15 reduction in time, as compared to native OpenPose, which would require a Graphical Processing Unit (GPU) to perform in real time. We further provide a design and implementation of a precision camera system consisting of two cameras in the frontal and lateral direction, which were precisely positioned using a laser cross. This system will be also used to verify whether the webcam is able to record with sufficient quality to further image processing analysis. As part of this work, a camera system including supporting calibration and recording scripts was designed and implemented. The cameras triggers were synchronized by wire interconnection and set up by proposed script. In this work we synchronize two cameras and align their frames such that the OpenPose can be applied independently to each of the two channels to measure movements from two different body projections (3D).