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Proceedings Paper

Toward Automatic Generation Of Object Recognition Program --- Modeling Sensors ---
Author(s): Katsushi Ikeuchi; Takeo Kanade
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Paper Abstract

A model-based vision system requires models in order to predict object appearances. How an object appears in the image is the result of interaction between the object properties and the sensor characteristics. Thus in model-based vision, we ought to model the sensor as well as the object. Previously, the sensor model was not used in model-based vision or, at least, was contained in the object model implicitly. This paper presents a framework between an object model and the object's appearances. We consider two aspects of sensor characteristics: sensor detectability and sensor reliability. Sensor detectability specifies what kinds of features can be detected and in what condition the features are detected; sensor reliability is a confidence for the detected features. We define the configuration space to represent sensor characteristics. We propose a representation method for sensor detectability and reliability in the configuration space. Finally, we investigate how to apply the sensor model to a model-based vision system, in particular, automatic generation of an object recognition program from a given model.

Paper Details

Date Published: 22 August 1988
PDF: 14 pages
Proc. SPIE 0938, Digital and Optical Shape Representation and Pattern Recognition, (22 August 1988); doi: 10.1117/12.976617
Show Author Affiliations
Katsushi Ikeuchi, Carnegie-Mellon University (United States)
Takeo Kanade, Carnegie-Mellon University (United States)


Published in SPIE Proceedings Vol. 0938:
Digital and Optical Shape Representation and Pattern Recognition
Richard D. Juday, Editor(s)

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