Ponencia
A Video Similarity Measure Combining Alignment, Graphical and Speech Features
Autor/es | Fuentes Brenes, Daniel
Bardeli, R. Ortega Ramírez, Juan Antonio González Abril, Luis |
Departamento | Universidad de Sevilla. Departamento de lenguajes y Sistemas Informáticos Universidad de Sevilla. Departamento de Economía Aplicada I |
Fecha de publicación | 2011-06 |
Fecha de depósito | 2023-05-24 |
ISBN/ISSN | 978-84-615-5513-0 |
Resumen | A large volume of video content on the web is available today, which demands efficient management. To effectively manage, search, retrieve and copy detection, similarity methods play a critica] role. In this paper, a novel ... A large volume of video content on the web is available today, which demands efficient management. To effectively manage, search, retrieve and copy detection, similarity methods play a critica] role. In this paper, a novel video similarity measure using visual fcatures, alignment distances and speech transcripts is proposed. Video files are represented by a sequence of segments set where each segment contains color histograms, start time and a set of syllables extracted from the speech in the audio track. In a first step, textual, alignment and visual features are extracted. They complement each other and can be further combined to boost the segment similarity. The second step describes how the Maximum Bipaitite Matching and sorne statistical features are. applied to find segments crnTespondences and calculate a global similarity value respectively. Experiments far video similarity were performed on a dataset and promising results were achieved to demonstrate the effectiveness of this method. |
Agencias financiadoras | Ministerio de Ciencia e Innovación (MICIN). España |
Identificador del proyecto | TIN2009-14378- C02-01 |
Ficheros | Tamaño | Formato | Ver | Descripción |
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A video similarity.pdf | 3.088Mb | [PDF] | Ver/ | |