The objective of this study was to assess the suitability of the Microsoft Kinect depth camera as a tool in segment scanning, segment tracking and player tracking. A mannequin was scanned with the Kinect and a laser scanner. The geometries were truncated to create torso ‘segments’ and compared. Separate shoulder abduction ( − 100° to 50°) and flexion motions (0°–100°) were recorded by the Kinect (using free and commercial software) and a Motion Analysis Corporation (MAC) system. Segment angles were compared. A participant's centre of mass (COM) was tracked over a 6 × 3 m floor area using the Kinect and a MAC system and compared. Mean errors with uncertainty of the mass, COM position and principal moments of inertia were − 1.9 ± 1.6%, 0.5 ± 0.4% and 3 ± 2.6%, respectively. The commercial software gave the highest accuracy, in which the maximum and root mean square errors (RMSEs) were 13.85° and 7.59° in abduction and 21.57° and 12.00° in flexion. RMSEs in X, Y and Z COM positions were 0.12, 0.14 and 0.08 m, respectively, although vertical position (Y) was subject to a large systematic bias of 405 mm. The Kinect's low cost and depth camera are an advantage for sports biomechanics and motion analysis. Although segment tracking accuracy is low, the Kinect could potentially be used in coaching and education for all three application areas in this study.

Three-dimensional surface imaging technologies have been used in the planning and evaluation of breast reconstructive and cosmetic surgery. The aim of this study was to develop a 3D surface imaging system based on the Microsoft Kinect and assess the accuracy and repeatability with which the system could image the breast. A system comprising two Kinects, calibrated to provide a complete 3D image of the mannequin was developed. Digital measurements of Euclidean and surface distances between landmarks showed acceptable agreement with manual measurements. The mean differences for Euclidean and surface distances were 1.9mm and 2.2mm, respectively. The system also demonstrated good intra- and inter-rater reliability (ICCs>0.999). The Kinect-based 3D surface imaging system offers a low-cost, readily accessible alternative to more expensive, commercially available systems, which have had limited clinical use.

The Microsoft Kinect is a cheap consumer device capable of markerless body segment tracking. While it was not originally designed for research applications, studies have been performed which utilise its capabilities. In order to better define the suitability of the device in a clinical and biomechanical context, a study was performed which assessed the accuracy of the device in 12 separate movements and for two different software-based tracking algorithms (IPIsoft and NITE). The movements were chosen to represent a variety of joint motions and speeds. Ten participants (height, 185 ± 6 cm; mass, 77 ± 9 kg) performed each movement while the Kinect and a Motion Analysis Corporation capture system recorded simultaneously. The procedure was performed twice, once for each tracking algorithm. Median values for RMSE, maximum error, systematic bias and proportional bias were 12.6°, 58.2°, 4.38° and 1.15°, respectively, for the IPIsoft algorithm and 13.8°, 63.1°, 3.16° and 1.19°, respectively, for the NITE algorithm. While maximum errors are high the system has many advantages over existing multi-camera markerless tracking systems. The Kinect could be used in low speed analysis of simple human motions where cost and ecological validity are of high priority.

KinectFusion is a typical three-dimensional reconstruction technique which enables generation of individual three-dimensional human models from consumer depth cameras for understanding body shapes. The aim of this study was to compare three-dimensional reconstruction results obtained using KinectFusion from data collected with two different types of depth camera (time-of-flight and stereoscopic cameras) and compare these results with those of a commercial three-dimensional scanning system to determine which type of depth camera gives improved reconstruction. Torso mannequins and machined aluminium cylinders were used as the test objects for this study. Two depth cameras, Microsoft Kinect V2 and Intel Realsense D435, were selected as the representatives of time-of-flight and stereoscopic cameras, respectively, to capture scan data for the reconstruction of three-dimensional point clouds by KinectFusion techniques. The results showed that both time-of-flight and stereoscopic cameras, using the developed rotating camera rig, provided repeatable body scanning data with minimal operator-induced error. However, the time-of-flight camera generated more accurate three-dimensional point clouds than the stereoscopic sensor. Thus, this suggests that applications requiring the generation of accurate three-dimensional human models by KinectFusion techniques should consider using a time-of-flight camera, such as the Microsoft Kinect V2, as the image capturing sensor.