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Real-Time Visual Tracking Insensitive to Three-Dimensional Rotation of Objects

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Biologically Motivated Computer Vision (BMCV 2000)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1811))

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Abstract

Visual tracking is essential for many applications such as vision-based control of intelligent robots, surveillance, agriculture automation, medical image processing, and so on. Especially, a fast and reliable visual tracking is important since the performance of visual tracking determines the reliability and real-time characteristics of overall system. It is not easy in visual tracking, however, to estimate the configuration of a target object in real-time when the three-dimensional pose of the target object is changing. On the contrary, a human being is able to track an object without the estimation of three-dimensional pose of the object even though three-dimensional rotations and /or occlusion by other objects change the original image of the object.

This paper proposes a fast and reliable SSD-based visual tracker insensitive to three-dimensional rotation of an object as well as translation, two-dimensional rotation, scaling, and shear of an object by proposing a performance measure for distortion of current image with respect to an original reference image. The performance measure is a combination of aspect ratio of a rectangle, variations of four internal angles of the rectangle from ninety degrees, the direction of rotation and the angular velocity of the rectangle. So, the reference image for visual tracking is updated whenever the performance measure is greater than an initialized distortion rate without the estimation of three-dimensional pose of an object. The algorithm is experimented in real-time successfully at a personal computer adopted with a general-purpose frame grabber.

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References

  1. T. Yamane, Y. Shirai, and J. Miura, “Person Tracking by Integrating Optical Flows and Uniform Brightness Regions”, Proceedings of IEEE International Conference on Robotics & Automation, pp. 3267–3272, 1998.

    Google Scholar 

  2. Y. Shirai, T. Yamane, R. Okada, “Robust Visual Tracking by Integrating Various Cues”, IEICE Transaction on Information & Systems, vol. E81-D, no. 9, pp. 951–958, 1998.

    Google Scholar 

  3. Natan Peterfreund, “Robust Tracking of Position and Velocity With Kalman Snakes”, IEEE Transaction on Pattern Analysis and Machine Intelligence, vol. 21, no. 6, pp. 564–569, 1999.

    Article  Google Scholar 

  4. Gregory D. Hager and Kentaro Toyama, “X Vision: A Portable Substrate for Real-Time Vision Applications”, Technical Report YALEU/DCS/RR-1078, 1997.

    Google Scholar 

  5. Gregory D. Hager and Peter N. Belhumeur, “Efficient Region Tracking With Parametric Models of Geometry and Illumination”, IEEE Transaction on Robotics and Automation, vol. 20, no. 10, pp. 1025–1038, 1998.

    Google Scholar 

  6. S.-W. Lee, B.-J. You, and G. D. Hager, “Model-based 3-D Object Tracking using Projective Invariance”, Proceedings of IEEE International Conference on Robotics and Automation, pp. 1589–1594, 1999.

    Google Scholar 

  7. A. J. Bray, “Tracking Objects using Image Disparities”, Image and Vision Computing, vol. 8, no. 1, pp. 4–9, 1990.

    Article  Google Scholar 

  8. D. B. Gennery, “Visual tracking of known three-dimensional objects”, International Journal of Computer Vision, vol. 7, no. 3, pp. 243–270, 1992

    Article  Google Scholar 

  9. D. G. Lowe, “Robust model-based motion tracking through the integration of search and estimation”, International Journal of Computer Vision, vol. 8, no. 2, pp. 113–122, 1992.

    Article  Google Scholar 

  10. R. S. Stephens, “Real-time 3D object tracking”, Image and Vision Computing, vol. 8, no. 1, pp. 4–9, 1990

    Article  Google Scholar 

  11. Nikolas P. Papanikolopoulos, Pradeep K. Khosla, and Takeo Kanade, “Visual Tracking of a Moving Target by a Camera Mounted on a Robot: A Combination of Control and Vision”, IEEE Transaction on Robotic and Automation, vol. 9, no. 1, 1993.

    Google Scholar 

  12. Kevin Nickels and Seth Hutchinson, “Measurement Error Estimation for Feature Tracking”, Proceedings of IEEE International Conference on Robotics and Automation, pp. 3230–3235, 1999.

    Google Scholar 

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© 2000 Springer-Verlag Berlin Heidelberg

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Cho, YJ., You, BJ., Lim, J., Oh, SR. (2000). Real-Time Visual Tracking Insensitive to Three-Dimensional Rotation of Objects. In: Lee, SW., Bülthoff, H.H., Poggio, T. (eds) Biologically Motivated Computer Vision. BMCV 2000. Lecture Notes in Computer Science, vol 1811. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45482-9_16

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  • DOI: https://doi.org/10.1007/3-540-45482-9_16

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-67560-0

  • Online ISBN: 978-3-540-45482-3

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