Generalized visual concept detection Genelleştirilmiş görsel kavram tanima

Date

2010-12-01

Author

Saracoǧlu, Ahmet
Tekin, Mashar
Esen, Ersin
Soysal, Medeni
Alatan, Abdullah Aydın
Ateş, Tuǧrul K.
Sevinç, A. Müge
Sevimli, Hakan
Acar, Banu Oskay
Zubari, Ünal
Ozan, Ezgi Can

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For efficient indexing and retrieval of video archives, concept detection stands as an important problem .In this work, a generalized structure that can be used for detection of diverse and distinct concepts is proposed. In the system, MPEG-7 Descriptors and Scale Invariant Transform (SIFT) are utilized as visual features. Furthermore, visual features are transformed by codebooks which are constructed by k-Means clustering. On the other hand, classification is performed on the distribution of visual features over the codebook. Proposed system is firstly tested against an elementary concept. Afterwards for a set of concepts system performance is reported on the TRECVID 2009 test set. It has been observed that with a sufficiently large training set high performance can be achieved with this method. ©2010 IEEE.

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https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=78651419508&origin=inward
https://hdl.handle.net/11511/106648

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Department of Electrical and Electronics Engineering, Conference / Seminar