https://oldena.lpnu.ua/handle/ntb/52444| Title: | Sequence Matching for Content-Based Video Retrieval |
| Authors: | Mashtalir, Sergii Mikhnova, Olena Stolbovyi, Mykhailo |
| Affiliation: | Kharkiv National University of Radio Electronics Kharkiv Petro Vasylenko National Technical University of Agriculture |
| Bibliographic description (Ukraine): | Mashtalir S. Sequence Matching for Content-Based Video Retrieval / Sergii Mashtalir, Olena Mikhnova, Mykhailo Stolbovyi // Data stream mining and processing : proceedings of the IEEE second international conference, 21-25 August 2018, Lviv. — Львів : Lviv Politechnic Publishing House, 2018. — P. 549–553. — (Machine Vision and Pattern Recognition). |
| Bibliographic description (International): | Mashtalir S. Sequence Matching for Content-Based Video Retrieval / Sergii Mashtalir, Olena Mikhnova, Mykhailo Stolbovyi // Data stream mining and processing : proceedings of the IEEE second international conference, 21-25 August 2018, Lviv. — Lviv Politechnic Publishing House, 2018. — P. 549–553. — (Machine Vision and Pattern Recognition). |
| Is part of: | Data stream mining and processing : proceedings of the IEEE second international conference, 2018 |
| Conference/Event: | IEEE second international conference "Data stream mining and processing" |
| Issue Date: | 28-Feb-2018 |
| Publisher: | Lviv Politechnic Publishing House |
| Place of the edition/event: | Львів |
| Temporal Coverage: | 21-25 August 2018, Lviv |
| Keywords: | Video Content Matching Spatio-Temporal Segmentation Set Theory Metric Space |
| Number of pages: | 5 |
| Page range: | 549-553 |
| Start page: | 549 |
| End page: | 553 |
| Abstract: | In this paper the authors propose a novel technique for comparing video frame sequence presented in an arbitrary metric space. By reviewing existing best practices in spatio-temporal video segmentation and frame matching, the authors suggest mathematical grounding for efficient video content analysis. Variants of relationships are observed between the frame sequences under comparison (perfect match, inclusion, equality of cardinality of sets). Examples of application as well as estimation metrics are also provided. |
| URI: | https://ena.lpnu.ua/handle/ntb/52444 |
| ISBN: | © Національний університет „Львівська політехніка“, 2018 © Національний університет „Львівська політехніка“, 2018 |
| Copyright owner: | © Національний університет “Львівська політехніка”, 2018 |
| URL for reference material: | https://www.igi-global.com/article/keyframe-extraction-from-video/115840 |
| References (Ukraine): | [1] D. Schonfeld, et. al., Video search and mining. Studies in Computational Intelligence. Springer, Berlin, 2010. [2] R. Szeliski, Computer vision. Algorithms and applications. Springer, London, 2011. [3] L. Chen, and F. W. M. Stentiford “Video sequence matching based on temporal ordinal measurement,” Pattern Recognition Letters., vol. 29, pp. 1824-1831, 2008. [4] S. Mashtalir, and O. Mikhnova, “Key frame extraction from video: framework and advances,” J. Computer Vision and Image Processing. vol. 4(2), pp. 67-78, 2014. (https://www.igi-global.com/article/keyframe-extraction-from-video/115840) [5] H. Lu, and Y.-P. Tan, “An effective post-refinement method for shot boundary detection,” IEEE Transactions on Circuits and Systems for Video Technology, vol. 15(11), pp. 1407–1421, November, 2005. [6] W. Heng, and K. Ngan, “Shot boundary refinement for long transition in digital video sequence”, IEEE Transactions on Multimedia, vol. 4(4), pp. 434-445, December, 2002. [7] A. F. Smeaton, P. Over, and A. R. Doherty, “Video shot boundary detection: Seven years of TRECVid activity,” J. Computer Vision and Image Understanding. vol. 114(4), pp. 411-418, 2010. [8] Zhang Y.-J. (ed.), Advances in image and video segmentation. Hershey- London-Melbourne-Singapore: IRM Press, 2006. [9] S. Porter, M. Mirmehdi, and B. Thomas, “Temporal video segmentation and classification of edit effects”, Image and Vision Computing., vol. 21, pp. 1097-1106, December 2003. [10] S. Piramanayagam, E. Saber, N. D. Cahill, and D. Messinger, “Shot boundary detection and label propagation for spatio-temporal video segmentation” Proc. SPIE 9405, Image Processing: Machine Vision Applications VIII, 94050D 7 p., February 2015. [11] S. Thakare, “Intelligent processing and analysis of image for shot boundary detection,” International Journal of Emerging Technology and Advanced Engineering., vol. 2, no. 2, pp. 208-212, Mar.-Apr. 2012. [12] R. Vázquez-Martín, and A. Bandera, “Spatio-temporal feature-based keyframe detection from video shots using spectral clustering,” Pattern Recognition Letters, vol. 34, no. 7, pp. 770-779, 2013. [13] G. I. Rathod, and D.A. Nikam, “An algorithm for shot boundary detection and key frame extraction using histogram difference,” Int. J. Emerging Technology and Advanced Engineering, vol. 3(8), pp. 155-163, August, 2013. [14] J. Nesvadba, F. Ernst, J. Perhavc, J. Benois-Pineau, and L. Primaux, “Comparison of shot boundary detectors”, Int. Conf. on Multimedia and Expo, IEEE Press, Amsterdam, pp. 6-8, 2005. [15] H. Jiang, G. Zhang, H. Wang and H. Bao, “Spatio-temporal video segmentation of static scenes and its applications” IEEE Transactions on Multimedia., vol. 17, no. 1, pp. 3-15, January, 2015. [16] Y. Bodyanskiy, D. Kinoshenko, S. Mashtalir, and O. Mikhnova, “Online video segmentation using methods of fault detection in multidimensional time sequences”, Int. J. of Electronic Commerce Studies, vol. 3(1), pp. 1-20, 2012. [17] O. Mikhnova, and N. Vlasenko, “Key frame partition matching for video summarization,” Int. J. of Information Models and Analyses, vol. 2(2), pp. 145-152, 2013. [18] C. D. Manning, P. Raghavan, and H. Schutze, Introduction to Information Retrieval. Cambridge University Press, Cambridge, 2008. [19] S. V. Mashtalir, and O. D. Mikhnova, “Stabilization of key frame descriptions with higher order Voronoi diagram”, J. Bionics of intelligence. vol. 1, pp. 68-72, 2013. |
| References (International): | [1] D. Schonfeld, et. al., Video search and mining. Studies in Computational Intelligence. Springer, Berlin, 2010. [2] R. Szeliski, Computer vision. Algorithms and applications. Springer, London, 2011. [3] L. Chen, and F. W. M. Stentiford "Video sequence matching based on temporal ordinal measurement," Pattern Recognition Letters., vol. 29, pp. 1824-1831, 2008. [4] S. Mashtalir, and O. Mikhnova, "Key frame extraction from video: framework and advances," J. Computer Vision and Image Processing. vol. 4(2), pp. 67-78, 2014. (https://www.igi-global.com/article/keyframe-extraction-from-video/115840) [5] H. Lu, and Y.-P. Tan, "An effective post-refinement method for shot boundary detection," IEEE Transactions on Circuits and Systems for Video Technology, vol. 15(11), pp. 1407–1421, November, 2005. [6] W. Heng, and K. Ngan, "Shot boundary refinement for long transition in digital video sequence", IEEE Transactions on Multimedia, vol. 4(4), pp. 434-445, December, 2002. [7] A. F. Smeaton, P. Over, and A. R. Doherty, "Video shot boundary detection: Seven years of TRECVid activity," J. Computer Vision and Image Understanding. vol. 114(4), pp. 411-418, 2010. [8] Zhang Y.-J. (ed.), Advances in image and video segmentation. Hershey- London-Melbourne-Singapore: IRM Press, 2006. [9] S. Porter, M. Mirmehdi, and B. Thomas, "Temporal video segmentation and classification of edit effects", Image and Vision Computing., vol. 21, pp. 1097-1106, December 2003. [10] S. Piramanayagam, E. Saber, N. D. Cahill, and D. Messinger, "Shot boundary detection and label propagation for spatio-temporal video segmentation" Proc. SPIE 9405, Image Processing: Machine Vision Applications VIII, 94050D 7 p., February 2015. [11] S. Thakare, "Intelligent processing and analysis of image for shot boundary detection," International Journal of Emerging Technology and Advanced Engineering., vol. 2, no. 2, pp. 208-212, Mar.-Apr. 2012. [12] R. Vázquez-Martín, and A. Bandera, "Spatio-temporal feature-based keyframe detection from video shots using spectral clustering," Pattern Recognition Letters, vol. 34, no. 7, pp. 770-779, 2013. [13] G. I. Rathod, and D.A. Nikam, "An algorithm for shot boundary detection and key frame extraction using histogram difference," Int. J. Emerging Technology and Advanced Engineering, vol. 3(8), pp. 155-163, August, 2013. [14] J. Nesvadba, F. Ernst, J. Perhavc, J. Benois-Pineau, and L. Primaux, "Comparison of shot boundary detectors", Int. Conf. on Multimedia and Expo, IEEE Press, Amsterdam, pp. 6-8, 2005. [15] H. Jiang, G. Zhang, H. Wang and H. Bao, "Spatio-temporal video segmentation of static scenes and its applications" IEEE Transactions on Multimedia., vol. 17, no. 1, pp. 3-15, January, 2015. [16] Y. Bodyanskiy, D. Kinoshenko, S. Mashtalir, and O. Mikhnova, "Online video segmentation using methods of fault detection in multidimensional time sequences", Int. J. of Electronic Commerce Studies, vol. 3(1), pp. 1-20, 2012. [17] O. Mikhnova, and N. Vlasenko, "Key frame partition matching for video summarization," Int. J. of Information Models and Analyses, vol. 2(2), pp. 145-152, 2013. [18] C. D. Manning, P. Raghavan, and H. Schutze, Introduction to Information Retrieval. Cambridge University Press, Cambridge, 2008. [19] S. V. Mashtalir, and O. D. Mikhnova, "Stabilization of key frame descriptions with higher order Voronoi diagram", J. Bionics of intelligence. vol. 1, pp. 68-72, 2013. |
| Content type: | Conference Abstract |
| Appears in Collections: | Data stream mining and processing : proceedings of the IEEE second international conference |
| File | Description | Size | Format | |
|---|---|---|---|---|
| 2018_Mashtalir_S-Sequence_Matching_for_549-553.pdf | 295.16 kB | Adobe PDF | View/Open | |
| 2018_Mashtalir_S-Sequence_Matching_for_549-553__COVER.png | 1.55 MB | image/png | View/Open |
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