Abstract
Tracking the pose of an object is a fundamental operation in computer vision. Yet, achieving this task for arbitrary objects without requiring a priori knowledge remains a major stumbling block. This paper introduces a method for tracking the pose of a moving object without requiring its 3D model or textured surfaces. In the first step, a sequence of images-poses pairs is obtained and PCA coefficients are derived from the image sequence. Then, a piecewise linear observation mapping is build between the poses and the PCA coefficients. The mapping is then used in the observation model of a Kalman filter that tracks the pose of the object.
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References
Black, M.J., Jepson, A.D.: EigenTracking: robust matching and tracking of articu lated objects using a view-based representation. IJCV 25 (1998) 63–84
Irani, M.: Multi-frame optical flow estimation using subspace constraints. ICCV (1999) 626–633
Jagersand, M.: Image based view synthesis of articulated agents. CVPR (1997) 1047–1053
Jolliffe, I.T.: Principal Component Analysis Springer, New York, (2002)
Linde, Y., Buzo, A., Gray, R.M.: An algorithm for vector quantizer design. IEEE Transactions on Communications (1980) 702–710
Lowe, D.G.: Fitting parameterized three-dimensional models to images. PAMI 13 (1991) 441–450
Murase, H., Nayar, S.K.: Visual learning and recognition of 3D objects from appearance. IJCV 14 (1995) 5–24
Nayar, S.K., Nene, S.A., Murase, H.: Subspace methods for robot vision. RA 12 (1996) 750–758
Shi, J., Tomasi, C: Good features to track. CVPR (1994) 593–600
Tomasi, C, Kanade, T.: Shape and motion from image streams under orthography: a factorization method. IJCV 9 (1992) 137–154
Turk, M., Pentland, A.P.: Eigenfaces for recognition. CogNeuro 3 (1991) 71–96
Welch, G., Bishop, G.: An introduction to the Kalman filter SIGGRAPH (2001) short course
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© 2003 Springer-Verlag Berlin Heidelberg
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Léonard, S., Jägersand, M. (2003). Tracking the Pose of Objects through Subspace. In: Bigun, J., Gustavsson, T. (eds) Image Analysis. SCIA 2003. Lecture Notes in Computer Science, vol 2749. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45103-X_51
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DOI: https://doi.org/10.1007/3-540-45103-X_51
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