https://oldena.lpnu.ua/handle/ntb/52438| Title: | Software for Visual Insect Tracking Based on F-transform Pattern Matching |
| Authors: | Hurtik, Petr Číž, David Kaláb, Oto Musiolek, David Kočárek, Petr Tomis, Martin |
| Affiliation: | University of Ostrava VSB-TU Ostrava |
| Bibliographic description (Ukraine): | Software for Visual Insect Tracking Based on F-transform Pattern Matching / Petr Hurtik, David Číž, Oto Kaláb, David Musiolek, Petr Kočárek, Martin Tomis // Data stream mining and processing : proceedings of the IEEE second international conference, 21-25 August 2018, Lviv. — Львів : Lviv Politechnic Publishing House, 2018. — P. 528–533. — (Machine Vision and Pattern Recognition). |
| Bibliographic description (International): | Software for Visual Insect Tracking Based on F-transform Pattern Matching / Petr Hurtik, David Číž, Oto Kaláb, David Musiolek, Petr Kočárek, Martin Tomis // Data stream mining and processing : proceedings of the IEEE second international conference, 21-25 August 2018, Lviv. — Lviv Politechnic Publishing House, 2018. — P. 528–533. — (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: | Gryllus Assimilis insect tracking visual tracking F-transform pattern matching 4k movie |
| Number of pages: | 6 |
| Page range: | 528-533 |
| Start page: | 528 |
| End page: | 533 |
| Abstract: | We introduce a problem of tracking small animals, especially insects. To solve this problem, we focus on visual tracking in recorded movies, propose our pattern tracking mechanism based on F-transform, and implement a user-friendly software to handle the movies. The tracking core is compared with five state-of-the-art tracking algorithms: KCF, MIL, TLD, Boosting and MedianFlow from processing time and algorithm failure rate point of views. Based on the results computed from 1000 movie frames, we observed that the proposed F-transform tracking core is the fastest and the most reliable method. |
| URI: | https://ena.lpnu.ua/handle/ntb/52438 |
| ISBN: | © Національний університет „Львівська політехніка“, 2018 © Національний університет „Львівська політехніка“, 2018 |
| Copyright owner: | © Національний університет “Львівська політехніка”, 2018 |
| References (Ukraine): | [1] R. Kays, M. C. Crofoot, W. Jetz, and M. Wikelski, “Terrestrial animal tracking as an eye on life and planet,” Science, vol. 348, no. 6240, p. aaa2478, 2015. [2] M. Wikelski, R. W. Kays, N. J. Kasdin, K. Thorup, J. A. Smith, and G. W. Swenson, “Going wild: what a global small-animal tracking system could do for experimental biologists,” Journal of Experimental Biology, vol. 210, no. 2, pp. 181–186, 2007. [3] A. W. Smeulders, D. M. Chu, R. Cucchiara, S. Calderara, A. Dehghan, and M. Shah, “Visual tracking: An experimental survey,” IEEE transactions on pattern analysis and machine intelligence, vol. 36, no. 7, pp. 1442–1468, 2014. [4] P. Hurtik and P. Stevuli ˇ akov ´ a, “Pattern matching: overview, benchmark ´ and comparison with f-transform general matching algorithm,” Soft Computing, vol. 21, no. 13, pp. 3525–3536, 2017. [5] M. Danelljan, F. Shahbaz Khan, M. Felsberg, and J. Van de Weijer, “Adaptive color attributes for real-time visual tracking,” in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Columbus, Ohio, USA, June 24-27, 2014. IEEE Computer Society, 2014, pp. 1090–1097. [6] F. S. Khan, J. Van de Weijer, and M. Vanrell, “Modulating shape features by color attention for object recognition,” International Journal of Computer Vision, vol. 98, no. 1, pp. 49–64, 2012. [7] Z. Kalal, K. Mikolajczyk, and J. Matas, “Tracking-learning-detection,” IEEE transactions on pattern analysis and machine intelligence, vol. 34, no. 7, pp. 1409–1422, 2012. [8] B. Babenko, M.-H. Yang, and S. Belongie, “Visual tracking with online multiple instance learning,” in Computer Vision and Pattern Recognition, 2009. CVPR 2009. IEEE Conference on. IEEE, 2009, pp. 983–990. [9] C. Ji and S. Ma, “Combinations of weak classifiers,” in Advances in Neural Information Processing Systems, 1997, pp. 494–500. [10] H. Grabner, M. Grabner, and H. Bischof, “Real-time tracking via on-line boosting.” in Bmvc, vol. 1, no. 5, 2006, p. 6. [11] H. Grabner and H. Bischof, “On-line boosting and vision,” in Computer Vision and Pattern Recognition, 2006 IEEE Computer Society Conference on, vol. 1. Ieee, 2006, pp. 260–267. [12] Z. Kalal, K. Mikolajczyk, and J. Matas, “Forward-backward error: Automatic detection of tracking failures,” in Pattern recognition (ICPR), 2010 20th international conference on. IEEE, 2010, pp. 2756–2759. [13] B. D. Lucas, T. Kanade et al., “An iterative image registration technique with an application to stereo vision,” IJCAI, vol. 81, p. 674–679, 1981. [14] P. Hurtik, P. Hodakov ´ a, and I. Perfilieva, “Approximate pattern matching ´ algorithm,” in International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems. Springer, 2016, pp. 577–587. [15] I. Perfilieva, “Fuzzy transforms: Theory and applications,” Fuzzy sets and systems, vol. 157, no. 8, pp. 993–1023, 2006. [16] D.-J. Jwo and S.-H. Wang, “Adaptive fuzzy strong tracking extended kalman filtering for gps navigation,” IEEE Sensors Journal, vol. 7, no. 5, pp. 778–789, 2007 |
| References (International): | [1] R. Kays, M. C. Crofoot, W. Jetz, and M. Wikelski, "Terrestrial animal tracking as an eye on life and planet," Science, vol. 348, no. 6240, p. aaa2478, 2015. [2] M. Wikelski, R. W. Kays, N. J. Kasdin, K. Thorup, J. A. Smith, and G. W. Swenson, "Going wild: what a global small-animal tracking system could do for experimental biologists," Journal of Experimental Biology, vol. 210, no. 2, pp. 181–186, 2007. [3] A. W. Smeulders, D. M. Chu, R. Cucchiara, S. Calderara, A. Dehghan, and M. Shah, "Visual tracking: An experimental survey," IEEE transactions on pattern analysis and machine intelligence, vol. 36, no. 7, pp. 1442–1468, 2014. [4] P. Hurtik and P. Stevuli ˇ akov ´ a, "Pattern matching: overview, benchmark ´ and comparison with f-transform general matching algorithm," Soft Computing, vol. 21, no. 13, pp. 3525–3536, 2017. [5] M. Danelljan, F. Shahbaz Khan, M. Felsberg, and J. Van de Weijer, "Adaptive color attributes for real-time visual tracking," in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Columbus, Ohio, USA, June 24-27, 2014. IEEE Computer Society, 2014, pp. 1090–1097. [6] F. S. Khan, J. Van de Weijer, and M. Vanrell, "Modulating shape features by color attention for object recognition," International Journal of Computer Vision, vol. 98, no. 1, pp. 49–64, 2012. [7] Z. Kalal, K. Mikolajczyk, and J. Matas, "Tracking-learning-detection," IEEE transactions on pattern analysis and machine intelligence, vol. 34, no. 7, pp. 1409–1422, 2012. [8] B. Babenko, M.-H. Yang, and S. Belongie, "Visual tracking with online multiple instance learning," in Computer Vision and Pattern Recognition, 2009. CVPR 2009. IEEE Conference on. IEEE, 2009, pp. 983–990. [9] C. Ji and S. Ma, "Combinations of weak classifiers," in Advances in Neural Information Processing Systems, 1997, pp. 494–500. [10] H. Grabner, M. Grabner, and H. Bischof, "Real-time tracking via on-line boosting." in Bmvc, vol. 1, no. 5, 2006, p. 6. [11] H. Grabner and H. Bischof, "On-line boosting and vision," in Computer Vision and Pattern Recognition, 2006 IEEE Computer Society Conference on, vol. 1. Ieee, 2006, pp. 260–267. [12] Z. Kalal, K. Mikolajczyk, and J. Matas, "Forward-backward error: Automatic detection of tracking failures," in Pattern recognition (ICPR), 2010 20th international conference on. IEEE, 2010, pp. 2756–2759. [13] B. D. Lucas, T. Kanade et al., "An iterative image registration technique with an application to stereo vision," IJCAI, vol. 81, p. 674–679, 1981. [14] P. Hurtik, P. Hodakov ´ a, and I. Perfilieva, "Approximate pattern matching ´ algorithm," in International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems. Springer, 2016, pp. 577–587. [15] I. Perfilieva, "Fuzzy transforms: Theory and applications," Fuzzy sets and systems, vol. 157, no. 8, pp. 993–1023, 2006. [16] D.-J. Jwo and S.-H. Wang, "Adaptive fuzzy strong tracking extended kalman filtering for gps navigation," IEEE Sensors Journal, vol. 7, no. 5, pp. 778–789, 2007 |
| Content type: | Conference Abstract |
| Appears in Collections: | Data stream mining and processing : proceedings of the IEEE second international conference |
| File | Description | Size | Format | |
|---|---|---|---|---|
| 2018_Hurtik_P-Software_for_Visual_Insect_528-533.pdf | 473.49 kB | Adobe PDF | View/Open | |
| 2018_Hurtik_P-Software_for_Visual_Insect_528-533__COVER.png | 1.62 MB | image/png | View/Open |
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