Asymptotic Performance Analysis of Bayesian Object Recognition

@inproceedings{Grenander1998AsymptoticPA,
  title={Asymptotic Performance Analysis of Bayesian Object Recognition},
  author={Ulf Grenander and Anuj Srivastava and Michael I. Miller},
  year={1998}
}
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

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