Surveillance Video Summarization Based on Histogram Differencing and Sum Conditional Variance
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 33122
Surveillance Video Summarization Based on Histogram Differencing and Sum Conditional Variance

Authors: Nada Jasim Habeeb, Rana Saad Mohammed, Muntaha Khudair Abbass

Abstract:

For more efficient and fast video summarization, this paper presents a surveillance video summarization method. The presented method works to improve video summarization technique. This method depends on temporal differencing to extract most important data from large video stream. This method uses histogram differencing and Sum Conditional Variance which is robust against to illumination variations in order to extract motion objects. The experimental results showed that the presented method gives better output compared with temporal differencing based summarization techniques.

Keywords: Temporal differencing, video summarization, histogram differencing, sum conditional variance.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1127042

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1698

References:


[1] Gao, Yue, and Qiong-Hai Dai. "Shot-based similarity measure for content-based video summarization." In Image Processing, 2008. ICIP 2008. 15th IEEE International Conference on, pp. 2512-2515. IEEE, 2008.
[2] Mahapatra, Ansuman, Pankaj K. Sa, Banshidhar Majhi, and Sudarshan Padhy. "MVS: A Multi-view video synopsis framework." Signal Processing: Image Communication (2016).
[3] Kuanar, Sanjay K., Rameswar Panda, and Ananda S. Chowdhury. "Video key frame extraction through dynamic Delaunay clustering with a structural constraint." Journal of Visual Communication and Image Representation 24.7 (2013): 1212-1227.
[4] Ejaz, Naveed, Irfan Mehmood, and Sung Wook Baik. "Efficient visual attention based framework for extracting key frames from videos." Signal Processing: Image Communication 28.1 (2013): 34-44.
[5] Ejaz, Naveed, et al. "Video Summarization by Employing Visual Saliency in a Sufficient Content Change Method." International Journal of Computer Theory and Engineering 6.1 (2014): 26.
[6] Al-Musawi, Nada and Saad Talib Hasson. "Improving Video Streams Summarization Using Synthetic Noisy Video Data." (IJACSA) International Journal of Advanced Computer Science and Applications, Vol. 6, No. 12, 2015.
[7] Gao, Yue, and Qiong-Hai Dai. "Shot-based similarity measure for content-based video summarization." Image Processing, 2008. ICIP 2008. 15th IEEE International Conference on. IEEE, 2008.
[8] Gygli, Michael, Helmut Grabner, and Luc Van Gool. "Video summarization by learning submodular mixtures of objectives." Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2015.
[9] Bhaumik, Hrishikesh, Siddhartha Bhattacharyya, and Susanta Chakraborty. "Redundancy Elimination in Video Summarization." Image Feature Detectors and Descriptors. Springer International Publishing, 2016. 173-202.
[10] Yang, Xue, and Zhicheng Wei. "Video segmentation and summarization based on Genetic Algorithm." Image and Signal Processing (CISP), 2011 4th International Congress on. Vol. 1. IEEE, 2011.
[11] Lei, Shaoshuai, Gang Xie, and Gaowei Yan. "A Novel Key-Frame Extraction Approach for Both Video Summary and Video Index." The Scientific World Journal 2014 (2014).
[12] Song, Xinhui, Li Sun, Jie Lei, Dapeng Tao, Guanhong Yuan, and Mingli Song. "Event-based large scale surveillance video summarization." Neurocomputing (2015).
[13] Wang, Yu, and Jun Kato. "A distance metric learning based summarization system for nursery school surveillance video." Image Processing (ICIP), 2012 19th IEEE International Conference on. IEEE, 2012.
[14] Li, Xuelong, Zhigang Wang, and Xiaoqiang Lu. "Surveillance Video Synopsis via Scaling Down Objects." (2016).
[15] Ren, Jinchang, Jianmin Jiang, and Yue Feng. "Activity-driven content adaptation for effective video summarization." Journal of Visual Communication and Image Representation 21.8 (2010): 930-938.
[16] astelo-Fernández, César, and Guillermo Calderón-Ruiz. "Automatic Video Summarization Using the Optimum-Path Forest Unsupervised Classifier." Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications. Springer International Publishing, 2015. 760-767.
[17] Lee, Yuan-Shan, Chia-Yung Hsu, Po-Chuan Lin, Chia-Yen Chen, and Jia-Ching Wang. "Video summarization based on face recognition and speaker verification." In Industrial Electronics and Applications (ICIEA), 2015 IEEE 10th Conference on, pp. 1821-1824. IEEE, 2015.
[18] Luo, Chu. "Video Summarization for Object Tracking in the Internet of Things." Next Generation Mobile Apps, Services and Technologies (NGMAST), 2014 Eighth International Conference on. IEEE, 2014.
[19] Shaikh, Soharab Hossain, Khalid Saeed, and Nabendu Chaki. "Moving Object Detection Approaches, Challenges and Object Tracking." Moving Object Detection Using Background Subtraction. Springer International Publishing, 2014. 5-14.
[20] Petersohn, Christian. Temporal video segmentation. Jörg Vogt Verlag, 2010.
[21] Delabarre, Bertrand, and Eric Marchand. "Visual servoing using the sum of conditional variance." Intelligent Robots and Systems (IROS), 2012 IEEE/RSJ International Conference on. IEEE, 2012.‏
[22] Maki, Atsuto, and Riccardo Gherardi. "Conditional variance of differences: A robust similarity measure for matching and registration." Structural, Syntactic, and Statistical Pattern Recognition. Springer Berlin Heidelberg, 2012. 657-665.‏
[23] Richa, R., Souza, M., Scandaroli, G., Comunello, E., & von Wangenheim, A. "Direct visual tracking under extreme illumination variations using the sum of conditional variance." Image Processing (ICIP), 2014 IEEE International Conference on. IEEE, 2014.‏
[24] Kevin Roebuck, “Data Deduplication: High-impact Strategies -What You Need to Know: Definitions, Adoptions, Impact, Benefits, Maturity, Vendors”, Emereo Publishing, 2012.
[25] Bendraou, Y., Essannouni, F., Aboutajdine, D., & Salam, A. "Video cut detection method based on a 2D luminance histogram using an appropriate threshold and a post processing." ‏ Wseas Transactions on Signal Processing, 2015.