Influence of a Marker-Based Motion Capture System on the Performance of Microsoft Kinect v2 Skeleton Algorithm

Abstract

Microsoft Kinect sensors are being widely used as low-cost marker-less motion capture systems in various kinematic studies. Previous studies investigated the reliability and validity of Microsoft Kinect sensors by employing marker-based motion capture systems. Both systems employ IR emitters and detectors to track human posture and physical activities. This paper hypothesizes that the motion capture systems may interfere with Microsoft Kinect One sensor and influence the sensor's performance in tracking the skeleton. Hence, this study investigated the impact of a motion capture system on the Microsoft Kinect v2 skeleton algorithm using a mannequin in the presence of eight Qualisys Oqus 300/310 cameras and retroreflective markers. It was found that the motion capture system introduced a destructive impact on the Microsoft Kinect v2 skeleton tracking algorithm. In addition, it was observed that retroreflective markers placed near the joints caused the Microsoft Kinect v2 to give an incorrect reading of estimate the joint position. The motion capture cameras thus caused a timevarying distortion of the Microsoft Kinect estimate of the joint position. It is believed that the inference can be reduced by decreasing the number of markers and avoiding facing the motion capture cameras in sight of Microsoft Kinect v2.

Design and Validation of Rule-Based Expert System by Using Kinect V2 for Real-Time Athlete Support

“…The operation of the depth sensor in Kinect works according to the 3D depth detection principle by sending IR (infrared) rays to the object in front of it and measuring the time taken for the reflected rays to return (time of flight) [57,58]. The 3D depth is calculated with the help of an algorithm belonging to Kinect running in the background and thus makes it possible to follow the skeleton of the users [59]. As shown in Figure 2, the data from here were used to express the 3D positions of the joints by vectors.…”

“…Users do their training at a distance of 2.5 m from Kinect, which is placed on a tripod 0.8-1.2 m high from the ground, as described in [33,59]. In addition, joint angles and inter-joint distances are calculated using the data obtained from skeletal extraction (see Section 2.3).…”

Physically Consistent Whole-Body Kinematics Assessment Based on an RGB-D Sensor. Application to Simple Rehabilitation Exercises

“…For an optimal field of view, the K2S was placed in front of the participant at 2.5 m and at 0.85 m above the floor, as recommended in the literature [30]. Moreover, the combined use of K2S and SS, both of which are infra-red sensors, might degrade the quality of K2S data [31]. Thus, the SS was not located in the direct field of view of the K2S and the participants were always less than 3 m away from the K2S.…”

Pose and motion capture technologies

“…Microsoft Kinect, the gesture sensitive controller was developed in 2010 using an RGB-D camera. Lately, the controller started being used for more than its original purpose, thus, the controller made for entertainment and gaming, started being used for motion capture howbeit it wasn't expressly designed to do so, not only MoCap being just one of the collection of plans it was used for, 3D scanning, stroke recovery, sign language communication, gesture based security, virtual reality interaction, virtual surface touchscreen applications and many more are already developed, as an aperture for its use in a diversity of domains, [4] including the proliferating towards inexorable hobbies of "lifelogging" (a term used for the activities in which people record their daily routines) [5] thus, also entering the domains of safety and security.…”