Abstract
RGB-D skeletons are nowadays commonly used e.g. for gesture recognition, and so their accuracy and stability have significant influence on further processing. Skeletons obtained with motion capture are considerably more accurate and can be used to assess the quality of RGB-D skeleton extraction algorithms. In this paper, we record motion sequences with both a Kinect RGB-D sensor and a full motion capture system and align the generated skeletons by subsequence dynamic time warping with a varied step size. To evaluate the alignment, we propose two measures: the minimum overall distance between feature vectors and the distance of transformed skeletons. Experimental results show that our proposed method provides a better alignment between skeletons than the comparison methods. The proposed technique can also be used for content-based retrieval from large motion capture databases.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Bautista, M., Hernández-Vela, A., Ponce, V., Perez-Sala, X., Baró, X., Pujol, O., Angulo, C., Escalera, S.: Probability-based dynamic time warping for gesture recognition on RGB-D data. In: International Workshop on Depth Image Analysis, Tsukuba Science City, Japan (2012)
Deng, L., Leung, H., Gu, N., Yang, Y.: Automated recognition of sequential patterns in captured motion streams. In: Chen, L., Tang, C., Yang, J., Gao, Y. (eds.) WAIM 2010. LNCS, vol. 6184, pp. 250–261. Springer, Heidelberg (2010)
Horn, B.K.P.: Closed-form solution of absolute orientation using unit quaternions. Journal of the Optical Society of America A 4(4), 629–642 (1987)
Kar, A.: Skeletal tracking using Microsoft Kinect. Methodology 1, 1–11 (2010)
Krishnamurthy, S.N.: Human Detection and Extraction using Kinect Depth Images. Master’s thesis, Bournemouth University, the United Kingdom (2011)
Lai, K., Konrad, J., Ishwar, P.: A gesture-driven computer interface using Kinect. In: Proc. Image Analysis and Interpretation (SSIAI 2012), pp. 185–188 (2012)
Menache, A.: Understanding motion capture for computer animation and video games. Morgan Kaufmann Pub. (2000)
Müller, M.: Information Retrieval for Music and Motion. Springer (2007)
Shen, W., Xiao, S., Jiang, N., Liu, W.: Unsupervised human skeleton extraction from Kinect depth images. In: Proc. 4th International Conference on Internet Multimedia Computing and Service (ICIMCS 2012), New York, USA, pp. 66–69 (2012)
Shotton, J., Fitzgibbon, A., Cook, M., Sharp, T., Finocchio, M., Moore, R., Kipman, A., Blake, A.: Real-time human pose recognition in parts from single depth images. In: Proc. Computer Vision and Pattern Recognition (June 2011)
Vieira, A., Lewiner, T., Schwartz, W., Campos, M.: Distance matrices as invariant features for classifying MoCap data. In: 21st International Conference on Pattern Recognition (ICPR), Tsukuba, Japan (2012)
Xia, L., Chen, C.C., Aggarwal, J.K.: Human detection using depth information by Kinect. In: Workshop on Human Activity Understanding from 3D Data in conjunction with CVPR (HAU3D), Colorado Springs, USA (2011)
Xia, L., Chen, C.C., Aggarwal, J.K.: View invariant human action recognition using histograms of 3D joints. In: CVPR Workshops, pp. 20–27. IEEE (2012)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Chen, X., Koskela, M. (2013). Sequence Alignment for RGB-D and Motion Capture Skeletons. In: Kamel, M., Campilho, A. (eds) Image Analysis and Recognition. ICIAR 2013. Lecture Notes in Computer Science, vol 7950. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39094-4_72
Download citation
DOI: https://doi.org/10.1007/978-3-642-39094-4_72
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-39093-7
Online ISBN: 978-3-642-39094-4
eBook Packages: Computer ScienceComputer Science (R0)