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  • 标题:Improving Video Streams Summarization Using Synthetic Noisy Video Data
  • 本地全文:下载
  • 作者:Nada Jasim Al-Musawi ; Saad Talib Hasson
  • 期刊名称:International Journal of Advanced Computer Science and Applications(IJACSA)
  • 印刷版ISSN:2158-107X
  • 电子版ISSN:2156-5570
  • 出版年度:2015
  • 卷号:6
  • 期号:12
  • DOI:10.14569/IJACSA.2015.061233
  • 出版社:Science and Information Society (SAI)
  • 摘要: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.
  • 关键词:thesai; IJACSA; thesai.org; journal; IJACSA papers; Video summarization; Histogram of Oriented Gradient (HOG); Correlation coefficients (R); key frames; illumination changes; noise; Random Numbers Generator function
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