Asymptotic Performance Analysis of Bayesian Object Recognition

  title={Asymptotic Performance Analysis of Bayesian Object Recognition},
  author={Ulf Grenander and Anuj Srivastava and Michael I. Miller},
This paper analyzes the performance of Bayesian object recognition algorithms in the context of deformable templates. Rigid CAD surface models represent the underlying targets; low-dimensional matrix Lie groups (rotation and translation) extend them to the particular instance of pose and position. For a target , I represents its templates and sI is the target template at the pose/location denoted by the parameter s. The remote sensors observing the objects are modeled by the projective… CONTINUE READING

From This Paper

Topics from this paper.


Publications referenced by this paper.
Showing 1-10 of 19 references

Inferences on Transformation Groups Generating Patterns on Rigid Motions

  • A. Srivastava
  • D. Sc. Thesis,
  • 1996
Highly Influential
4 Excerpts

On some simple estimates of atr performance, and initial comparisons for a small data set

  • F. Garber, E. Zelnio
  • In Proceedings of SPIE,
  • 1997
1 Excerpt

Atr performance using enhanced resolution sar

  • L. M. Novak, G. R. Benitz, G. J. Owirka, L. A. Bessette
  • In Proceedings of SPIE,
  • 1996
1 Excerpt

Evaluation of sar atr

  • A. C. Williams, B. Clark
  • In Proceedings of SPIE,
  • 1996
1 Excerpt

Similar Papers

Loading similar papers…