Abstract
Human motion analysis is an increasingly important active research domain with various applications in surveillance, human-machine interaction and human posture analysis. The recent developments in depth sensor technology, especially with the release of the Kinect device, have attracted significant attention to the question of how to take advantage of this technology in order to achieve accurate motion tracking and action detection in marker-less approaches. In this paper, we review the benefits and limitations deriving from the adoption of structured light-based depth sensors in human motion analysis applications. Surveying the relevant literature, we have identified in calibration, interference and bias correction the challenges to tackle for an effective adoption of multi-Kinect systems to improve the visual analysis of human movement.
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References
Aggarwal, J.K., Cai, Q.: Human motion analysis: a review. Comput. Vis. Image Underst. 73(3), 428–440 (1999)
Moeslund, T.B., Granum, E.: A Survey of Computer Vision-Based Human Motion Capture. Comput. Vis. Image Underst. 18, 231–268 (2001)
Wang, L., Hu, W.: Recent developments in human motion analysis. Pattern Recognition 36(3), 585–601 (2003)
Herda, L., Urtasun, R., Fua, P.: Hierarchical Implicit Surface Joint Limits to Constrain Video-Based Motion Capture. In: Pajdla, T., Matas, J(G.) (eds.) ECCV 2004. LNCS, vol. 3022, pp. 405–418. Springer, Heidelberg (2004)
Cerveri, P., Pedotti, A.: Robust recovery of human motion from video using Kalman filters and virtual humans. Human Movement Science 22(3), 377–404 (2003)
Microsoft. Kinect for X-BOX 360 (2010), http://www.xbox.com/en-US/kinect
Poppe, R.: Vision-based human motion analysis: an overview. Comput. Vis. Image Underst. 108(1-2), 4–18 (2007)
Kehl, R., Van Gool, L.: Marker-less tracking of complex human motions from multiple views. Comput. Vis. Image Underst. 104(2), 190–209 (2006)
Ji, X., Liu, H.: Advances in view-invariant human motion analysis: a review. Trans. Sys. Man Cyber Part C 40(1), 13–24 (2010)
Moeslund, T.B., Hilton, A., Kruger, V.: A survey of advances in vision-based human motion capture and analysis. Comput. Vis. Image Underst. 104(2), 90–126 (2006)
Wang, L., Hu, W., Tan, T.: Recent developments in human motion analysis. Pattern Recognition 36(3), 585–601 (2003)
Smisek, J., Jancosek, M.: 3D with Kinect. In: 2011 IEEE International Conference on Computer Vision Workshops, pp. 1154–1160. IEEE Press, New York (2011)
Hartmann, J., Forouher, D., Litza, M., Klüssendorff, J.H., Maehle, E.: Real-time visual SLAM using FastSLAM and the Microsoft Kinect Camera. ROBOTIK (2012)
Clark, R.A., Bryant, A.L.: Validity of the Microsoft Kinect for assessment of postural control. Gait & Posture (2012)
Gallo, L., Placitelli, A.P., Ciampi, M.: Controller-free exploration of medical image data: experiencing the Kinect. In: 24th IEEE CBMS, pp. 1–6. IEEE, Los Alamitos (2011)
Berger, K., Ruhl, K.: Markless capture using multiple color-depth sensors. In: 2011 Workshop on Vision, Modeling, and Visualization, pp. 317–324. Eurographics Association (2011)
Maimone, A., Fuchs, H.: Enhanced personal autostereoscopic telepresence system using commodity depth camera. Computers & Graphics (2012)
Maimone, A., Fuchs, H.: Reducing interference between multiple structured light depth sensors using motion. In: 2012 IEEE Virtual Reality Workshops, pp. 51–54. IEEE Press, New York (2012)
Gallo, L., Minutolo, A.: Design and comparative evaluation of Smoothed Pointing: a velocity-oriented remote pointing enhancement technique. Int. J. of Human-Computer Studies 70(4), 287–300 (2012)
Burrus, N.: RGB Demo project (2011), http://labs.manctl.com/rgbdemo
Konolige, K., Mihelich, P.: Technical description of Kinect calibration. Tech. Rep., Willow Garage (2011), http://www.ros.org/wiki/kinect_calibration/technical
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Essmaeel, K., Gallo, L., Damiani, E., De Pietro, G., Dipandà, A. (2012). Multiple Structured Light-Based Depth Sensors for Human Motion Analysis: A Review. In: Bravo, J., Hervás, R., Rodríguez, M. (eds) Ambient Assisted Living and Home Care. IWAAL 2012. Lecture Notes in Computer Science, vol 7657. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35395-6_33
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DOI: https://doi.org/10.1007/978-3-642-35395-6_33
Publisher Name: Springer, Berlin, Heidelberg
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