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Security is value, which become more and more desirable while we must note dramatically increasing quantity and weight of numerous dangers related to particular persons, to different populations and to almost everybody and everywhere. Therefore we can observe up-to-date fast and massive increase of social requisition in the area of protection against terroristic attacks and hapless random events. Even fanatic privacy defenders, who in the past often protested against surveillance, now must take into account scale of threats which is generated by actual political and social tensions, and must agree for inconsiderable limitations of privacy (in public space) when it is connected with huge increase of public security. Therefore now the question is not whether oversee of human behavior in public space – but how to do it?
Słowa kluczowe
Wydawca
Czasopismo
Rocznik
Tom
Strony
48--51
Opis fizyczny
Bibliogr. 7 poz., fot., rys.
Twórcy
autor
- Akademia Górniczo-Hutnicza, Katedra Automatyki i Inżynierii Biomedycznej
Bibliografia
- [1] Baltieri D., Vezzani R., Cucchiara R.: 3dpes: 3D people dataset for surveillance and forensics, in Proceedings of the 1st International ACM Workshop on Multimedia access to 3D Human Objects, 2011.
- [2] Chmiel W., Kwiecień J., Mikrut Z.: Realization of scenarios for video surveillance. „Image Processing & Communications”, Vol. 17, No 4, 2012, pp. 231-240.
- [3] Fischler M.A., Bolles R.C.: Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography, Communications of the ACM, 1981, 24(6): 381-395.
- [4] Hirzer M., Beleznai C., Roth P.M., Bischof H.: Person re-identification by descriptive and discriminative classification. SCI A, LNCS. vol. 6688, pp. 91-102, 2011.
- [5] Huang J., Yang X., Fang X., et al.: Integrating visual saliency and consistency for re-ranking image search results. IEEE Transactions on Multimedia, 13(4): 653-661, 2011.
- [6] Kryjak T. (ed.): SIMPOZ final research rapport (volumes 1 and 2), AGH, Krakow 2013.
- [7] Shen X., Lin Z., Brandt J., et al.: Object retrieval and localization with spatially-constrained similarity measure and k-NN re-ranking. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 3013-3020, 2012.
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Bibliografia
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