Active Foreground Region Extraction and Tracking for Sports Video Annotation
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http://hdl.handle.net/10045/39277
Título: | Active Foreground Region Extraction and Tracking for Sports Video Annotation |
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Autor/es: | Mentzelopoulos, Markos | Psarrou, Alexandra | Angelopoulou, Anastassia | Garcia-Rodriguez, Jose |
Grupo/s de investigación o GITE: | Informática Industrial y Redes de Computadores |
Centro, Departamento o Servicio: | Universidad de Alicante. Departamento de Tecnología Informática y Computación |
Palabras clave: | Background subtraction | Object detection | Spatial correlation | Parametric and non-parametric approaches | Sports video | Dominant color | Clustering |
Área/s de conocimiento: | Arquitectura y Tecnología de Computadores |
Fecha de publicación: | feb-2013 |
Editor: | Springer Science+Business Media New York |
Cita bibliográfica: | Neural Processing Letters. 2013, 37(1): 33-46. doi:10.1007/s11063-012-9267-4 |
Resumen: | Automatic video segmentation plays a vital role in sports videos annotation. This paper presents a fully automatic and computationally efficient algorithm for analysis of sports videos. Various methods of automatic shot boundary detection have been proposed to perform automatic video segmentation. These investigations mainly concentrate on detecting fades and dissolves for fast processing of the entire video scene without providing any additional feedback on object relativity within the shots. The goal of the proposed method is to identify regions that perform certain activities in a scene. The model uses some low-level feature video processing algorithms to extract the shot boundaries from a video scene and to identify dominant colours within these boundaries. An object classification method is used for clustering the seed distributions of the dominant colours to homogeneous regions. Using a simple tracking method a classification of these regions to active or static is performed. The efficiency of the proposed framework is demonstrated over a standard video benchmark with numerous types of sport events and the experimental results show that our algorithm can be used with high accuracy for automatic annotation of active regions for sport videos. |
URI: | http://hdl.handle.net/10045/39277 |
ISSN: | 1370-4621 (Print) | 1573-773X (Online) |
DOI: | 10.1007/s11063-012-9267-4 |
Idioma: | eng |
Tipo: | info:eu-repo/semantics/article |
Derechos: | The final publication is available at Springer via http://dx.doi.org/10.1007/s11063-012-9267-4 |
Revisión científica: | si |
Versión del editor: | http://dx.doi.org/10.1007/s11063-012-9267-4 |
Aparece en las colecciones: | INV - I2RC - Artículos de Revistas INV - AIA - Artículos de Revistas |
Archivos en este ítem:
Archivo | Descripción | Tamaño | Formato | |
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2013_Mentzelopoulos_etal_NPL_final.pdf | Versión final (acceso restringido) | 1,06 MB | Adobe PDF | Abrir Solicitar una copia |
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