Improving Kinect-Skeleton Estimation
| Authors | |
|---|---|
| Year of publication | 2015 |
| Type | Article in Proceedings |
| Conference | Advanced Concepts for Intelligent Vision Systems (ACIVS 2015), LNCS 9386 |
| MU Faculty or unit | |
| Citation | |
| Doi | http://dx.doi.org/10.1007/978-3-319-25903-1_50 |
| Field | Informatics |
| Keywords | Kinect v2; skeleton proportions; bone length estimation; joint accuracy |
| Description | Capturing human movement activities through various sensor technologies is becoming more and more important in entertainment, film industry, military, healthcare or sports. The Microsoft Kinect is an example of low-cost capturing technology that enables to digitize human movement into a 3D motion representation. However, the accuracy of this representation is often underestimated which results in decreasing effectiveness of Kinect applications. In this paper, we propose advanced post-processing methods to improve the accuracy of the Kinect skeleton estimation. By evaluating these methods on real-life data we decrease the error in accuracy of measured lengths of bones more than two times. |
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