For monitoring public domains, surveillance
camera systems are used. Reviewing and processing any
subsequences from large amount of raw video streams is time
and space consuming. Many efficient approaches of video
summarization were proposed to reduce the amount of irrelevant
information. Most of these approaches do not take into
consideration the illumination or lighting changes that cause
noise in video sequences. In this work, video summarization
algorithm for video streams has been proposed using Histogram
of Oriented Gradient and Correlation coefficients techniques.
This algorithm has been applied on the proposed multi-model
dataset which is created by combining the original data and the
dynamic synthetic data. This dynamic data is proposed using
Random Number Generator function. Experiments on this
dataset showed the effectiveness of the proposed algorithm
compared with traditional dataset
Publication Date
11/12/2015
Publisher
International Journal of Advanced Computer Science and Applications
ندى جاسم حبيب | Nada Al-Musawi | 10380