Is the MS Kinect suitable for motion analysis?

Abstract

IntroductionInvestigating human motion with expensive and accurate optical marker based systems has been the state of the art since long ago. However, markerless low-cost systems have always been a desideratum in the field of biomechanics and sports science. Due to increasing computer chip power and the corresponding progress in image processing techniques the realization of such a system has become feasible. With the advent of the Microsoft Kinect sensor in 2011 a flexible low-cost tool has entered the computer game market that enables markerless tracking of human motion. At first sight the Kinect provides an amazing accuracy. The goal of the present work is to quantitatively investigate the tracking accuracy of the Kinect sensor by studying the human gait cycle on a treadmill. The Kinect results are compared with data stemming from a VICON system which is regarded as a kind of gold standard in terms of spatial resolution. Subsequently, a post processing step is applied to the Kinect data using anthropometric data as a priori information in order to enhance Kinect's tracking results. MethodsThe Kinect sensor provides a skeleton model whose measured joint positions and segment lengths only roughly match those of the VICON system. A first inspection of the measurements reveals that segment lengths determined by the Kinect system are considerably varying in time (up to +/-20% at the most). In order to freeze the length of all segments the Levenberg-Marquardt-algorithm (LMA) is applied to the Kinect data. LMA manipulates the Kinect joint positions such that the segment lengths of the Kinect skeleton to be become identical with pre-defined lengths. These segment length of the original human being can easily be determined by previous manual measurements. In our special case we use the data provided by the VICON system. ResultsThe comparison between both systems shows that the Kinect sensor is currently not able to provide anthropometrically reliable segment lengths. However, this failure of the Kinect system is healed with our above described optimization procedure. When looking at the angles relevant for the human gait cycle the Kinect sensor provides astonishing accuracy. The curves describing the time dependency of those angles are very similar when comparing the data from both systems (except for a small scaling factor). The shapes of these curves are only marginally affected by our optimization process. ConclusionOur work shows that the Kinect sensor is already capable of describing the motion of walking and running with acceptable accuracy in the frontal plane. Additionally it is proved that a posteriori optimization using a priori available knowledge can further improve the tracking of the anatomical landmarks. That does not mean the Kinect sensor is now ready for use in highly sophisticated scientific applications, but it can already be applied for basic research in simple clinical test cases. It is expected that regarding both accuracy and measurement frequency the near future will see significant improvemen...

Reliability and validity of the Microsoft Kinect for assessment of manual wheelchair propulsion

“…This pilot study is consistent with previous literature comparing the Kinect and a three-dimensional goldstandard alternative in the assessment of postural control and gait [30][31]51]. Along with the present study, previ ous research has suggested varied accuracy across out comes and unreliable body segment lengths affecting accuracy of joint positioning.…”

Bayesian classification and analysis of gait disorders using image and depth sensors of Microsoft Kinect

“…1 allows us to record data sets that can be further processed in the appropriate mathematical environment using methods and algorithms for motion anal- ysis [9,[18][19][20], gesture recognition [21] and robotic systems control [22,23]. Selected data acquired from image and depth sensors are presented in Figs.…”

Interception of moving objects in karate: an experimental, marker-free benchmark

“…As other low cost devices 10 , this scanner (the Microsoft Kinect) is an interesting technology which uses patterned light to derive the depth of different segments of the human body without external markers. This device has been previously validated for postural control 11 , for personalization of exercises 12 , foot posture 13 , hand tracking 14,15 . Here we applied this technology to the study of movement reproducibility of skilled karate as in a natural setup, using an unconstrained catching task.…”