Related Experiment Video
Updated: Aug 5, 2026

Movement Retraining using Real-time Feedback of Performance
Published on: January 17, 2013
Influence of camera geometry on 3D joint angle estimation in markerless motion capture
Xiong Zhao1, Yan Zhang2, Ryan B Graham1
1School of Human Kinetics, Faculty of Health Sciences, University of Ottawa, Ottawa, Ontario, Canada.
Objectives:
This study examined how camera geometry influences the agreement of two-camera markerless joint-angle estimates with an eight-camera markerless reference system.
Methods:
Twenty-three female soccer athletes completed pre-season Y-balance, L-hop, countermovement jump, broad jump, and bodyweight squat tasks. Movements were recorded using an eight-camera Theia3D markerless system as the reference. All 28 two-camera combinations were processed using a custom Pose2Sim-based pipeline to estimate lower-limb joint angles. Camera geometry was quantified from calibration data, including camera height, distance to origin, azimuth, field of view, and horizontal angular separation. Agreement with the reference system and consistency among two-camera configurations were assessed using root mean square error (RMSE), mean absolute error (MAE), bias, limits of agreement, and coefficient of multiple correlation (CMC).
Results:
Agreement varied by camera geometry, anatomical plane, and task. Front and Back configurations, with moderate horizontal angular separation values of 68.59 ± 17.68° and 80.95 ± 22.35°, generally showed more favorable agreement, particularly for sagittal-plane hip and knee kinematics (RMSE < 8°, CMC ≈ 1.00). Same Quadrant configurations had the smallest angular separation (28.24 ± 3.81°) and poorer agreement, especially for frontal- and transverse-plane angles (RMSE > 10°, CMC < 0.60). Diagonal configurations had the largest angular separation (160.56 ± 13.40°) but did not consistently improve agreement. Y-balance and L-hop showed reduced agreement and higher dropout due to self-occlusion and participants moving outside the field of view.
Conclusion:
Camera geometry influenced two-camera markerless motion capture agreement. Front and Back configurations with moderate angular separation were most suitable for sagittal-dominant bilateral tasks, whereas Same Quadrant configurations should be avoided. For Y-balance and L-hop, camera placement should prioritize foot/ankle visibility and full movement-path coverage rather than angular separation alone.
Related Concept Videos
Relative Motion Analysis using Rotating Axes
However, to express the relative position of point B relative to point A, an additional frame of reference, denoted as x'y', is necessary. This additional frame not only translates but also rotates relative to the fixed frame, making it instrumental in...
Kinematic Equations for Rotation
For instance, imagine a point A on a rigid body engaged in circular motion. The translational velocity of this particular point can be calculated by taking the time derivatives of the displacement equation, which essentially measures the...
Relative Motion Analysis using Rotating Axes-Problem Solving
Here, in order to determine the magnitude of velocity and acceleration for point...
Absolute Motion Analysis- General Plane Motion
As the drone's propellers rotate, an upward force is generated that counteracts the force of gravity, enabling the drone to lift off from the ground. This initial movement of the drone is along a straight path, representing a form of translational motion. In this phase, every point on the drone...
Kinematic Equations - III
Using the kinematic equations,...
Kinematic Equations - II
Suppose a car merges into freeway traffic on a 200 m long ramp. If its initial velocity is 10 m/s and it accelerates at 2 m/s2, then the...