Abstract
Pose estimation in the context of human motion analysis is the process of approximating the body configuration in each frame of a motion sequence. We propose a novel pose estimation method based on fitting a skeletal model to tree structures built from skeletonised visual hulls reconstructed from multi-view video. The pose is estimated independently in each frame, hence the method can recover from errors in previous frames, which overcomes some problems of tracking. Publically available datasets were used to evaluate the method. On real data the method performs at a framerate of \(\sim\!14\) fps. Using synthetic data the positions of the joints were determined with a mean error of \(\sim\!6\) cm.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Bakken, R.H.: Using Synthetic Data for Planning, Development and Evaluation of Shape-from-Silhouette Based Human Motion Capture Methods. In: Proceedings of ISVC (2012)
Bakken, R.H., Hilton, A.: Real-Time Pose Estimation Using Tree Structures Built from Skeletonised Volume Sequences. In: Proceedings of VISAPP, pp. 181–190 (2012)
Buss, S.R.: Introduction to Inverse Kinematics with Jacobian Transpose, Pseudoinverse and Damped Least Squares Methods (2004) (unpublished manuscript), http://math.ucsd.edu/~sbuss/ResearchWeb
Caillette, F., Galata, A., Howard, T.: Real-time 3-D human body tracking using learnt models of behaviour. Computer Vision and Image Understanding 109(2), 112–125 (2008)
Chen, Y.-L., Chai, J.: 3D Reconstruction of Human Motion and Skeleton from Uncalibrated Monocular Video. In: Zha, H., Taniguchi, R.-i., Maybank, S. (eds.) ACCV 2009, Part I. LNCS, vol. 5994, pp. 71–82. Springer, Heidelberg (2010)
Gkalelis, N., Kim, H., Hilton, A., Nikolaidis, N., Pitas, I.: The i3DPost multi-view and 3D human action/interaction database. In: Proceedings of the Conference for Visual Media Production, pp. 159–168 (2009)
Guerra-Filho, G.: A General Motion Representation - Exploring the Intrinsic Viewpoint of a Motion. In: Proceedings of GRAPP, pp. 347–352 (2012)
Kastenmeier, T., Vesely, F.: Numerical robot kinematics based on stochastic and molecular simulation methods. Robotica 14(03), 329–337 (1996)
Menier, C., Boyer, E., Raffin, B.: 3D Skeleton-Based Body Pose Recovery. In: Proceedings of 3DPVT, pp. 389–396 (2006)
Michoud, B., Guillou, E., Bouakaz, S.: Real-Time and Markerless 3D Human Motion Capture Using Multiple Views. In: Elgammal, A., Rosenhahn, B., Klette, R. (eds.) Human Motion 2007. LNCS, vol. 4814, pp. 88–103. Springer, Heidelberg (2007)
Moeslund, T.B., Hilton, A., Krüger, V.: A survey of advances in vision-based human motion capture and analysis. Computer Vision and Image Understanding 104, 90–126 (2006)
Moschini, D., Fusiello, A.: Tracking Human Motion with Multiple Cameras Using an Articulated Model. In: Gagalowicz, A., Philips, W. (eds.) MIRAGE 2009. LNCS, vol. 5496, pp. 1–12. Springer, Heidelberg (2009)
Poppe, R.: Vision-based human motion analysis: An overview. Computer Vision and Image Understanding 108(1-2), 4–18 (2007)
Straka, M., Hauswiesner, S., Rüther, M., Bischof, H.: Skeletal Graph Based Human Pose Estimation in Real-Time. In: Proceedings of BMVC (2011)
Sundaresan, A., Chellappa, R.: Model-driven segmentation of articulating humans in Laplacian Eigenspace. IEEE Transactions on Pattern Analysis and Machine Intelligence 30(10), 1771–1785 (2008)
Tang, W., Cavazza, M., Mountain, D., Earnshaw, R.: A constrained inverse kinematics technique for real-time motion capture animation. The Visual Computer 15(7-8), 413–425 (1999)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Bakken, R.H., Hilton, A. (2012). Real-Time Pose Estimation Using Constrained Dynamics. In: Perales, F.J., Fisher, R.B., Moeslund, T.B. (eds) Articulated Motion and Deformable Objects. AMDO 2012. Lecture Notes in Computer Science, vol 7378. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31567-1_4
Download citation
DOI: https://doi.org/10.1007/978-3-642-31567-1_4
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-31566-4
Online ISBN: 978-3-642-31567-1
eBook Packages: Computer ScienceComputer Science (R0)