Robust tracking with spatio-velocity snakes: Kalman filtering approach

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Description

Using results from robust Kalman filtering, the author presents a new Kalman filter-based snake model for tracking of nonrigid objects in combined spatio-velocity space. The proposed model is the stochastic version of the velocity snake, an active contour model for combined tracking of position and velocity of nonrigid boundaries. The proposed model uses image gradient and optical flow measurements along the contour as system measurements. An optical-flow based measurement error is used to detect and reject image measurements which correspond to image clutter or to other objects. The method was applied to object tracking of both rigid and nonrigid objects, ... continued below

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26 p.

Creation Information

Peterfreund, N. June 1, 1997.

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  • Oak Ridge National Laboratory
    Publisher Info: Oak Ridge National Lab., Center for Engineering Systems Advanced Research, TN (United States)
    Place of Publication: Tennessee

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Description

Using results from robust Kalman filtering, the author presents a new Kalman filter-based snake model for tracking of nonrigid objects in combined spatio-velocity space. The proposed model is the stochastic version of the velocity snake, an active contour model for combined tracking of position and velocity of nonrigid boundaries. The proposed model uses image gradient and optical flow measurements along the contour as system measurements. An optical-flow based measurement error is used to detect and reject image measurements which correspond to image clutter or to other objects. The method was applied to object tracking of both rigid and nonrigid objects, resulting in good tracking results and robustness to image clutter, occlusions and numerical noise.

Physical Description

26 p.

Notes

OSTI as DE98005995

Source

  • Other Information: PBD: Jun 1997

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  • Other: DE98005995
  • Report No.: ORNL/TM--13449
  • Grant Number: AC05-96OR22464
  • DOI: 10.2172/631266 | External Link
  • Office of Scientific & Technical Information Report Number: 631266
  • Archival Resource Key: ark:/67531/metadc693858

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Creation Date

  • June 1, 1997

Added to The UNT Digital Library

  • Aug. 14, 2015, 8:43 a.m.

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  • Nov. 3, 2016, 6:46 p.m.

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Peterfreund, N. Robust tracking with spatio-velocity snakes: Kalman filtering approach, report, June 1, 1997; Tennessee. (digital.library.unt.edu/ark:/67531/metadc693858/: accessed September 21, 2017), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.