Background Subtraction for Time of Flight Imaging
A time of flight camera provides two types of images simultaneously, depth and intensity. In this paper a computational method for background subtraction, combining both images or fast sequences of images, is proposed. The background model is based on unbalanced or semi-supervised classifiers, in pa...
| Autores: | , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión enviada para evaluación y publicación |
| Fecha de publicación: | 2017 |
| País: | Argentina |
| Institución: | Comisión de Investigaciones Científicas de la Provincia de Buenos Aires |
| Repositorio: | CIC Digital (CICBA) |
| Idioma: | inglés |
| OAI Identifier: | oai:digital.cic.gba.gob.ar:11746/8579 |
| Acceso en línea: | https://digital.cic.gba.gob.ar/handle/11746/8579 |
| Access Level: | acceso abierto |
| Palabra clave: | Ingenierías y Tecnologías industrial TOF cameras machine vision pattern recognition support vector machines |
| Sumario: | A time of flight camera provides two types of images simultaneously, depth and intensity. In this paper a computational method for background subtraction, combining both images or fast sequences of images, is proposed. The background model is based on unbalanced or semi-supervised classifiers, in particular support vector machines. A brief review of one class support vector machines is first given. A method that combines the range and intensity data in two operational modes is then provided. Finally, experimental results are presented and discussed. |
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