The ability to understand human movement is beneficial for deciding surgical procedures, tracking disease progression over time and helping with patient rehabilitation. The current gold-standard for collecting human movement is the use of 3-dimensional marker-based systems. Several studies have presented the many limitations to the current gold-standard that reduces the number of people who are able to benefit from a gait analysis. Those limitations in the current gold-standard include the requirements of large laboratory space, costly equipment, long instrumentation and collection time, and the potential for motion artifact from markers being placed on the skin. The purpose of this study is to create a marker-less motion capture system using the newly–released Kinect Azure cameras from Microsoft. The study aims to validate the new system against the gold-standard. A validation of a four Kinect Azure camera system was conducted with 10 subjects completing over ground walking trials at a self-selected pace, sit-to-stand, lunge, and step up/down while Kinect and 3D marker-based data were collected simultaneously. The data was synchronized and cut to a single activity cycle where joint angles and spatio-temporal measures were compared between the two systems. Walking speed and stride length were highly correlated between the two systems with r-values >0.9 and p-values <0.001. The average difference in maximum knee flexion angle between the two systems is 2.84with a r=0.785 and p-value <0.001. A 3D point cloud was generated from the four Kinect Azure camera system to generate a surface mesh. The 3D mesh was used to provide a better understanding of body habitus than current BMI.