Paper
6 October 1998 Active object recognition using appearance-based representations derived from solid geometric models
Michael A. Sipe, David P. Casasent
Author Affiliations +
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 3D 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.
© (1998) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Michael A. Sipe and David P. Casasent "Active object recognition using appearance-based representations derived from solid geometric models", Proc. SPIE 3522, Intelligent Robots and Computer Vision XVII: Algorithms, Techniques, and Active Vision, (6 October 1998); https://doi.org/10.1117/12.325758
Lens.org Logo
CITATIONS
Cited by 3 scholarly publications.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Error analysis

Cameras

Ray tracing

Solids

Active vision

Image processing

Detection and tracking algorithms

Back to Top