Object recognition
Object recognition entails identifying instances of known objects in sensory data by searching for a match between features in a scene and features on a model. The key elements that make object recognition feasible are the use of diverse sensory input forms such as stereo imagery or range data, appr...
| Autores: | , |
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| Tipo de recurso: | capítulo de libro |
| Fecha de publicación: | 2007 |
| País: | España |
| Institución: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/2669 |
| Acceso en línea: | https://hdl.handle.net/2117/2669 |
| Access Level: | acceso abierto |
| Palabra clave: | Computer vision Pattern recognition systems Artificial intelligence Automatic guided vehicles Image segmentation Image sensors Object setection Robot sision Stereo image processing Visió per ordinador Reconeixement de formes (Informàtica) Classificació INSPEC::Pattern recognition::Computer vision Classificació INSPEC::Pattern recognition::Object recognition Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Processament del senyal::Processament de la imatge i del senyal vídeo Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Processament del senyal::Reconeixement de formes |
| Sumario: | Object recognition entails identifying instances of known objects in sensory data by searching for a match between features in a scene and features on a model. The key elements that make object recognition feasible are the use of diverse sensory input forms such as stereo imagery or range data, appropriate low level processing of the sensory input, clever object representations, and good algorithms for scene-to-model hypothesis generation and model matching. Whether data acquisition takes place using video images or range sensors, an object recognition system must pre-process the sensory data for the extraction of relevant features in the scene. Once a feature vector is obtained, the problem now is that of correspondence. Provided a training session has taken place, a search for a match between model features and scene features is performed. A consistent match and the corresponding transformation give a solution to the problem of object recognition. |
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