A Bayesian Approach to Object Identification in Pattern Recognition

We present a new Bayesian approach to object identification: variants. By object identification we mean the detection of the member (regular variant) of a given statistical population (model) among a group of observations (variants). We present estimators for selecting the regular variant, which (i) depend on the knowledge of the regular population and on a suitable reference measure, only, (ii) are simple to evaluate, and (iii) are optimal, i. e., Bayesian under certain conditions. Moreover, we combine variant selection with Bayesian classification considering the situation where we observe

• Type: Conference
• Year: 2000
• Where: ICPR
• Authors: Gunter Ritter, María Teresa Gallegos
• Keywords: Computer Vision, ICPR 2000, Object Identification, Regular Variants, Suitable Reference Measures