DMCA
Active Object Recognition Using Appearance-based Representations Derived from Solid Geometric Models (1998)
| Venue: | in Symposium on Intelligent Systems and Advanced Manufacturing, vol. 3522, Proc. SPIE |
| Citations: | 2 - 2 self |
BibTeX
@INPROCEEDINGS{Sipe98activeobject,
author = {Michael A. Sipe and David Casasent},
title = {Active Object Recognition Using Appearance-based Representations Derived from Solid Geometric Models},
booktitle = {in Symposium on Intelligent Systems and Advanced Manufacturing, vol. 3522, Proc. SPIE},
year = {1998},
pages = {139--150}
}
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Abstract
We present new test results for our active object recognition algorithms. The algorithms are used to classify and estimate the pose of objects in different stable rest positions and automatically re-position the camera if the class or pose of an object is ambiguous in a given image. Multiple object views are now used in determining both the final object class and pose estimate; previously, multiple views were used for classification only. A feature space trajectory (FST) in eigenspace is used to represent 3-D distorted views of an object. FSTs are constructed using images rendered from solid models. We discuss lighting and material settings for photorealism in the rendering process. The FSTs are analyzed to determine the camera positions that best resolve ambiguities. Real objects are recognized from intensity images using the FST representation derived from rendered imagery. Key Words: active object recognition, active vision, Bayesian estimation, pose estimation 1 Introduction Acti...
Keyphrases
solid geometric model multiple object view new test result rendering process different stable rest position final object class resolve ambiguity pose estimate solid model active object recognition introduction acti multiple view bayesian estimation pose estimation intensity image camera position active object recognition algorithm fst representation real object 3-d distorted view active vision feature space trajectory material setting key word
