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Título: | A syntactical approach to learn and identify bidimensional image models |
Autor: | Saínz, Miguel; Sanfeliu, Alberto CSIC ORCID | Palabras clave: | Automatic learning Generic multi-purpose model Grammatica inference Augmented regular expressions Context sensitive grammars Pattern recognition: Computer vision Computer vision |
Fecha de publicación: | 1997 | Editor: | Asociación Española de Reconocimientos de Formas y Análisis de Imágenes | Citación: | 7th Spanish Symposium on Pattern Recognition and Image Analysis: 1-3 (1997) | Resumen: | In one hand, automatic generation of models from a set of positive and negative samples and a-priori knowledge (if available) is a crucial issue for pattern recongnition applications. In the other hand, a generic multipurpose 2D object model representation is very useful in object recognition in complex scenes. In this paper we present a new approach of 2D objects multi-purpose model model representation based in context sensitive language and automatic learning. To illustrate the model representation of the performances achieved two different applications have been developed: an outdoor traffic sign identifier and a human face identifier. Partial results of the recognition process of both applications are shown. | Descripción: | Spanish Symposium on Pattern Recognition and Image Analysis (SNRFAI), 1997, Barcelona (España) | URI: | http://hdl.handle.net/10261/30183 |
Aparece en las colecciones: | (IRII) Comunicaciones congresos |
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