3D object recognition based on hierarchical eigen shapes and Bayesian inference

Timo Kostiainen; Ilkka Kalliomaeki; Toni Tamminen; Jouko Lampinen

doi:10.1117/12.444179

5 October 2001 3D object recognition based on hierarchical eigen shapes and Bayesian inference

Timo Kostiainen, Ilkka Kalliomaeki, Toni Tamminen, Jouko Lampinen

Proceedings Volume 4572, Intelligent Robots and Computer Vision XX: Algorithms, Techniques, and Active Vision; (2001) https://doi.org/10.1117/12.444179
Event: Intelligent Systems and Advanced Manufacturing, 2001, Boston, MA, United States

Abstract

We present results of using Bayesian inference for recovering the 3D shape and texture of an object based on information extracted from a single 2D image. We are using a number of different models for specific object classes. The goal is to combine the classes to a hierarchical structure. Instead of searching for the most probable explanation we estimate the entire posterior distribution of the model parameters using Markov chain Monte Carlo methods. The evaluation of model fit is based on combining edge information with intensity difference between the model and the target image.

Citation Download Citation

Timo Kostiainen, Ilkka Kalliomaeki, Toni Tamminen, and Jouko Lampinen "3D object recognition based on hierarchical eigen shapes and Bayesian inference", Proc. SPIE 4572, Intelligent Robots and Computer Vision XX: Algorithms, Techniques, and Active Vision, (5 October 2001); https://doi.org/10.1117/12.444179

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