10.11

Statistical Models of Targets and Clutter for Use in Bayesian Object Recognition

Anuj Srivastava,     Florida State University

Michael I. Miller,     Johns Hopkins University

Ulf Grenander,     Brown University

1 Introduction

2 Statistical Models

2.1 Target Representations

2.2 Sensor Modeling

2.3 Clutter Models

3 Bayesian Framework

4 Pose Location Estimation and Performance

4.1 Minimum Mean Squared Error Estimator

4.2 Lower bound on Expected Error

5 Target Recognition and Performance

6 Discussion

7 Acknowledgment

References

1 Introduction

When human beings look at camera images of known objects, such as a table, a chair, a human face, or a car, we recognize them immediately. For example, Fig. 1 shows several images of tanks ...

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