Automatic Feature-Based Stabilization of Video with Intentional Motion through a Particle Filter

Blanco Adán, Carlos Roberto del; Jaureguizar Núñez, Fernando; Salgado Álvarez de Sotomayor, Luis y García Santos, Narciso (2009). Automatic Feature-Based Stabilization of Video with Intentional Motion through a Particle Filter. En: "10th International Conference on Advanced Concepts for Intelligent Vision Systems, ACIVS 2008", 20/10/2008-24/10/2008, Juan-les-Pins, Francia. ISBN 978-3-540-88457-6.

Descripción

Título: Automatic Feature-Based Stabilization of Video with Intentional Motion through a Particle Filter
Autor/es:
  • Blanco Adán, Carlos Roberto del
  • Jaureguizar Núñez, Fernando
  • Salgado Álvarez de Sotomayor, Luis
  • García Santos, Narciso
Tipo de Documento: Ponencia en Congreso o Jornada (Artículo)
Título del Evento: 10th International Conference on Advanced Concepts for Intelligent Vision Systems, ACIVS 2008
Fechas del Evento: 20/10/2008-24/10/2008
Lugar del Evento: Juan-les-Pins, Francia
Título del Libro: Proceedings of 10th International Conference on Advanced Concepts for Intelligent Vision Systems, ACIVS 2008
Fecha: 2009
ISBN: 978-3-540-88457-6
Volumen: Lectur
Materias:
Escuela: E.T.S.I. Telecomunicación (UPM)
Departamento: Señales, Sistemas y Radiocomunicaciones
Licencias Creative Commons: Reconocimiento - Sin obra derivada - No comercial

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Resumen

Video sequences acquired by a camera mounted on a hand held device or a mobile platform are affected by unwanted shakes and jitters. In this situation, the performance of video applications, such us motion segmentation and tracking, might dramatically be decreased. Several digital video stabilization approaches have been proposed to overcome this problem. However, they are mainly based on motion estimation techniques that are prone to errors, and thus affecting the stabilization performance. On the other hand, these techniques can only obtain a successfully stabilization if the intentional camera motion is smooth, since they incorrectly filter abrupt changes in the intentional motion. In this paper a novel video stabilization technique that overcomes the aforementioned problems is presented. The motion is estimated by means of a sophisticated feature-based technique that is robust to errors, which could bias the estimation. The unwanted camera motion is filtered, while the intentional motion is successfully preserved thanks to a Particle Filter framework that is able to deal with abrupt changes in the intentional motion. The obtained results confirm the effectiveness of the proposed algorithm

Más información

ID de Registro: 3711
Identificador DC: http://oa.upm.es/3711/
Identificador OAI: oai:oa.upm.es:3711
URL Oficial: http://www.springerlink.com/content/4531m05172r53156/
Depositado por: Memoria Investigacion
Depositado el: 06 Abr 2011 11:13
Ultima Modificación: 20 Abr 2016 13:12
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