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Scalable object-based video retrieval in HD video databases / Cl. Morand in Signal processing. Image communication, Vol. 25 N° 6 (Juillet 2010) 

Public ISBD [article]  in Signal processing. Image communication > Vol. 25 N° 6 (Juillet 2010) . - pp. 450–465 Titre : Scalable object-based video retrieval in HD video databases Type de document : texte imprimé Auteurs : Cl. Morand, Auteur ; J. Benois-Pineau, Auteur ; J.-Ph. Domenger, Auteur Année de publication : 2012 Article en page(s) : pp. 450–465 Note générale : Electronique Langues : Anglais (eng) Mots-clés : HD  video  Scalable  video  object  extraction  Object-based  indexing  Video  retrieval Résumé : With exponentially growing quantity of video content in various formats, including the popularisation of HD (High Definition) video and cinematographic content, the problem of efficient indexing and retrieval in video databases becomes crucial. Despite efficient methods have been designed for the frame-based queries on video with local features, object-based indexing and retrieval attract attention of research community by the seducing possibility to formulate meaningful queries on semantic objects. In the case of HD video, the principle of scalability addressed by actual compression standards is of great importance. It allows for indexing and retrieval on the lower resolution available in the compressed bit-stream. The wavelet decomposition used in the JPEG2000 standard provides this property. In this paper, we propose a scalable indexing of video content by objects. First, a method for scalable moving object extraction is designed. Using the wavelet data, it relies on the combination of robust global motion estimation with morphological colour segmentation at a low spatial resolution. It is then refined using the scalable order of data. Second, a descriptor is built only on the objects extracted. This descriptor is based on multi-scale histograms of wavelet coefficients of objects. Comparison with SIFT features extracted on segmented object masks gives promising results. ISSN : 0923-5965 En ligne : http://www.sciencedirect.com/science/article/pii/S0923596510000482 [article] Scalable object-based video retrieval in HD video databases [texte imprimé] / Cl. Morand, Auteur ; J. Benois-Pineau, Auteur ; J.-Ph. Domenger, Auteur . - 2012 . - pp. 450–465. Electronique Langues : Anglais (eng) in Signal processing. Image communication > Vol. 25 N° 6 (Juillet 2010) . - pp. 450–465 Mots-clés : HD  video  Scalable  video  object  extraction  Object-based  indexing  Video  retrieval Résumé : With exponentially growing quantity of video content in various formats, including the popularisation of HD (High Definition) video and cinematographic content, the problem of efficient indexing and retrieval in video databases becomes crucial. Despite efficient methods have been designed for the frame-based queries on video with local features, object-based indexing and retrieval attract attention of research community by the seducing possibility to formulate meaningful queries on semantic objects. In the case of HD video, the principle of scalability addressed by actual compression standards is of great importance. It allows for indexing and retrieval on the lower resolution available in the compressed bit-stream. The wavelet decomposition used in the JPEG2000 standard provides this property. In this paper, we propose a scalable indexing of video content by objects. First, a method for scalable moving object extraction is designed. Using the wavelet data, it relies on the combination of robust global motion estimation with morphological colour segmentation at a low spatial resolution. It is then refined using the scalable order of data. Second, a descriptor is built only on the objects extracted. This descriptor is based on multi-scale histograms of wavelet coefficients of objects. Comparison with SIFT features extracted on segmented object masks gives promising results. ISSN : 0923-5965 En ligne : http://www.sciencedirect.com/science/article/pii/S0923596510000482