Abstract
Joint advent of affordable color and depth sensors and super-realtime skeleton detection, has produced a surge of research on Human Motion Capture. They provide a very important key to communication between Man and Machine. But the design was willing and closed-loop interaction, which allowed approximations and mandates a particular sensor setup. In this paper, we present a multiple sensor-based approach, designed to augment the robustness and precision of human joint positioning, based on delayed logic and filtering, of skeleton detected on each sensor.
The original version of this chapter was revised: The copyright line was incorrect. This has been corrected. The Erratum to this chapter is available at DOI: 10.1007/978-3-319-02895-8_64
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Masse, JT., Lerasle, F., Devy, M., Monin, A., Lefebvre, O., Mas, S. (2013). Human Motion Capture Using Data Fusion of Multiple Skeleton Data. In: Blanc-Talon, J., Kasinski, A., Philips, W., Popescu, D., Scheunders, P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2013. Lecture Notes in Computer Science, vol 8192. Springer, Cham. https://doi.org/10.1007/978-3-319-02895-8_12
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DOI: https://doi.org/10.1007/978-3-319-02895-8_12
Publisher Name: Springer, Cham
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