We present a human body motion tracking system for an interactive virtual simulation training environment. This system captures images using IR illumination and near-IR cameras to overcome limitations of a dimly lit environment. Features, such as silhouettes and medial axis of blobs are extracted from the images which lack much internal texture. We use a combination of a 2D ICP and particle filtering method to estimate the articulated body configuration of a trainee from image features. The method allows articulation of the arms at elbows and shoulders and of the body at the waist; this is a considerable improvement over previous such methods. Our system works in real-time and is robust to temporary errors in image acquisition or tracking. The system serves as part of a multi-modal user-input device for interactive simulation. © 2008 Springer-Verlag.
CITATION STYLE
Chu, C. W., & Nevatia, R. (2008). Real-time 3D body pose tracking from multiple 2D images. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5098 LNCS, pp. 42–52). https://doi.org/10.1007/978-3-540-70517-8_5
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