Content Based Video Retrieval using SURF Descriptor


Autoria(s): Sreeraj, M; Asha, S
Data(s)

30/07/2014

30/07/2014

29/08/2013

Resumo

This paper presents a Robust Content Based Video Retrieval (CBVR) system. This system retrieves similar videos based on a local feature descriptor called SURF (Speeded Up Robust Feature). The higher dimensionality of SURF like feature descriptors causes huge storage consumption during indexing of video information. To achieve a dimensionality reduction on the SURF feature descriptor, this system employs a stochastic dimensionality reduction method and thus provides a model data for the videos. On retrieval, the model data of the test clip is classified to its similar videos using a minimum distance classifier. The performance of this system is evaluated using two different minimum distance classifiers during the retrieval stage. The experimental analyses performed on the system shows that the system has a retrieval performance of 78%. This system also analyses the performance efficiency of the low dimensional SURF descriptor.

2013 Third International Conference on Advances in Computing and Communications

Identificador

http://dyuthi.cusat.ac.in/purl/4316

Idioma(s)

en

Publicador

IEEE

Palavras-Chave #Shot Boundary Detection #Feature Extraction #SURF Descriptor #Fuzzy K Nearest Neighbor
Tipo

Article