Abstract
In this paper, we report a robust, efficient, and automatic method for matching infrared tracked markers for human motion analysis in computer-aided physical therapy applications. The challenges of this task stem from non-rigid marker motion, occlusion, and timing requirements. To overcome these difficulties, we use pair-wise distance constraints for marker identification. To meet the timing requirements, we first reduce the candidate marker labels by proximity constraints before enforcing the pair-wise constraints. Experiments with 38 real motion sequences, our method has shown superior accuracy and significant speedup over a semi-automatic proprietary method and the Iterative Closest Point (ICP) approach.
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References
Besl, P.J., McKay, N.D.: A Method for Registration of 3-D Shapes. PAMI 14, 239–256 (1992)
Broida, T.J., Chellappa, R.: Estimation of Object Motion Parameters from a Sequence of Noisy Images. PAMI 8, 90–99 (1986)
Isard, M., Blake, A.: Condensation - conditional density propagation for visual tracking. IJCV 29, 5–28 (1998)
Dorfmuller-Ulhaas, K.: Robust optical user motion tracking using a kalman filter. In: ACM VRST (2003)
Herda, L., Fua, P., Plankers, R., Boulic, R., Thalmann, D.: Skeleton-based motion capture for robust reconstruction of human motion. In: Proc. Computer Animation (2000)
Hornung, A., Sar-Dessai, S., Kobbelt, L.: Self-calibrating optical motion tracking for articulated bodies. IEEE Virtual Reality, 75–82 (2005)
Kato, H., Billinghurst, M.: Marker tracking and HMD calibration for a video-based augmented reality conferencing system. In: Int’l Wshp on Augmented Reality, pp. 85–94 (1999)
Keshner, E.A., Kenyon, R.V.: Using immersive technology for postural research and rehabilitation. Assist Technol. Summer 16(1), 54–62 (2004)
Kurihara, K., Hoshino, S., Yamane, K., Nakamura, Y.: Optical motion capture system with pan-tilt camera tracking and real time data processing. In: ICRA, vol. 2 (2002)
van Liere, R., van Rhijn, A.: Search space reduction in optical tracking. In: Proceedings of the Workshop on Virtual Environments, pp. 207–214 (2003)
Ringer, M., Lasenby, J.: A procedure for automatically estimating model parameters in optical motion capture. Image and Vision Computing 22, 843–850 (2004)
Tolani, D., Goswami, A., Badler, N.I.: Real-time inverse kinematics techniques for anthropomorphic limbs. Graphical models 62, 353–388 (1999)
Welch, G., Bishop, G., Vicci, L., Brumback, S., Keller, K.: The HiBall tracker: High-performance wide-area tracking for virtual and augmented environments. In: ACM VRST (1999)
Yilmaz, A., Javed, O., Shah, M.: Object Tracking: A Survey. ACM Computing Surveys 38(4) (2006)
Zordan, V.B., Van Der Horst, N.C.: Mapping optical motion capture data to skeletal motion using a physical model. In: ACM symp. on Computer Animation, pp. 245–250 (2003)
Salari, V., Sethi, I.K.: Feature point correspondence in the presence of occlusion. PAMI 12(1), 87–91 (1990)
Sethi, I., Jain, R.: Finding trajectories of feature points in a monocular image sequence. PAMI 9(1), 56–73 (1987)
Rangarajan, K., Shah, M.: Establishing motion correspondence. In: Conference Vision Graphies Image Process, vol. 54(1), pp. 56–73 (1991)
Intille, S., Davis, J., Bobick, A.: Real-time closed-world tracking. In: CVPR, pp. 697–703 (1997)
Veenman, C., Reinders, M., Backer, E.: Resolving motion correspondence for densely moving points. PAMI 23(1), 54–72 (2001)
Shafique, K., Shah, M.: A non-iterative greedy algorithm for multi-frame point correspondence. In: ICCV, pp. 110–115 (2003)
Zhang, Z.: Iterative point matching for registration of free-form curves and surfaces. IJCV 13, 119–152 (1994)
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Johnson, G., Xie, N., Slaboda, J., Shi, Y.J., Keshner, E., Ling, H. (2010). Efficient Marker Matching Using Pair-Wise Constraints in Physical Therapy. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2010. Lecture Notes in Computer Science, vol 6454. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17274-8_22
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DOI: https://doi.org/10.1007/978-3-642-17274-8_22
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-17273-1
Online ISBN: 978-3-642-17274-8
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