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Automated and intelligent video surveillance systems play important role in the modern world. Since the amount of various video streams that must be analyzed grows, such artificial intelligence systems can assist humans in performing tiresome tasks. As a result, the effectiveness of response to a dangerous situations is increasing (detect unexpected movement or unusual behavior that may pose a threat to people, property and infrastructure). Video surveillance systems have to meet several requirements: must be accurate and not produce too many false alarms, moreover it must be able to process the received video stream in real-time to provide a sufficient response time. The work presented here focuses on the selected challenges of scene analysis in video surveillance systems (object detection/tracking, effectiveness of the whole system). The aim of the research is to design a low-budget surveillance system, that can be used for example in a home security monitoring. Such solution can be use not only to surveillance but also to monitor elderly person at home or provide new ways of interacting in human-computer interaction systems.
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Czasopismo
Rocznik
Tom
Strony
91--99
Opis fizyczny
Bibliogr. 12 poz., rys.
Twórcy
autor
- AGH University of Science and Technology, al. Mickiewicza 30, 30-059 Kraków
Bibliografia
- [1] PETS, Ninth IEEE International Workshop on Performance Evaluation of Tracking and Surveillance- PETS 2006 Benchmark Data, 2006
- [2] F. Bashir and F. Porikli, Performance evaluation of object detection and tracking systems, In IEEE InternationalWorkshop on Performance Evaluation of Tracking and Surveillance (PETS), June 2006
- [3] T Bouwmans, Recent advanced statistical background modeling for foreground detection: A systematic survey, Recent Patents on Computer Science, vol. 4, no. 3, 2011
- [4] W. Chmiel, J. Kwiecien, Z. Mikrut, Realization of scenarios for video surveillance, In Image Processing & Communications, vol. 17, pp. 231-240, 2013
- [5] C Lakshmi Devasena, R Revathí, M Hemalatha, Video surveillance systems-a survey, IJCSI International Journal of Computer Science Issues, vol. 8, no. 4, pp. 1694-0814, 2011
- [6] Kinjal A Joshi and Darshak G Thakore, A survey on moving object detection and tracking in video surveillance system. International Journal of Soft Computing and Engineering (IJSCE) ISSN, pp. 2231-2307, 2012
- [7] Y. Keselman, S. Dickinson, Bridging the representation gap between models and exemplars, In Proceedings, IEEE Workshop on Models versus Exemplars in Computer Vision. Citeseer, 2001
- [8] T. Kryjak, Shadow removal for greyscale video sequences, In Seminarium: Przetwarzanie i analiza sygnałów w systemach wizji i sterowania - Slok., 2012
- [9] T. Kryjak, M. Komorkiewicz, M. Gorgon, Implementation of a background generation algorithm with moving object detection and shadow suppressing in spartan 6 series fpga devices (in polish), Automatyka: półrocznik Akademii Gorniczo-Hutniczej im. Stanislawa Staszica w Krakowie, vol. 15, no. 3, pp. 197-217, 2011
- [10] Z. Mikrut, P. Pleciak, M. Smolen, Combining pattern matching and optical flow methods in home care vision system, In Information Technologies in Biomedicine, pp. 537-548, Springer, 2012
- [11] J. Przybyło, Automatic adaptation of humancomputer interaction system, Pomiary, Automatyka, Robotyka, vol. 15, no. 12, pp. 86-88, 2011
- [12] C. Stauffer, W.E.L. Grimson, Adaptive background mixture models for real-time tracking, In Computer Vision and Pattern Recognition, 1999, IEEE Computer Society Conference on., IEEE, vol. 2, 1999
Typ dokumentu
Bibliografia
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