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.
Description:
2013 Third International Conference on Advances in Computing and Communications