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Elastic Shape Models for Interpolations of Curves in Image Sequences

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Information Processing in Medical Imaging (IPMI 2005)

Abstract

Many applications in image analysis are concerned with the temporal evolution of shapes in video sequences. In situations involving low-contrast, low-quality images, human aid is often needed to extract shapes from images. An interesting approach is to use expert help to extract shapes in certain well-separated frames, and to use automated methods to extract shapes from intermediate frames. We present a technique to interpolate between expert generated shapes. This technique preserves salient features in the interpolated shapes, and allows analysts to model a continuous evolution of shapes, instead of a coarse sampling generated by the expert. The basic idea is to establish a correspondence between points on the two end shapes, and to construct a geodesic flow on a shape space maintaining that correspondence. This technique is demonstrated using echocardiagraphic images and infrared human gait sequences.

Research supported in part by (FRG) DMS-0101429 and ARO W911 NF-04-01-0268.

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© 2005 Springer-Verlag Berlin Heidelberg

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Joshi, S.H., Srivastava, A., Mio, W. (2005). Elastic Shape Models for Interpolations of Curves in Image Sequences. In: Christensen, G.E., Sonka, M. (eds) Information Processing in Medical Imaging. IPMI 2005. Lecture Notes in Computer Science, vol 3565. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11505730_45

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  • DOI: https://doi.org/10.1007/11505730_45

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-26545-0

  • Online ISBN: 978-3-540-31676-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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