Real-time implementation of moving object detection in video surveillance systems using FPGA

• Autorzy: Kryjak T. , Gorgoń M.

Warianty tytułu

PL

Implementacja detekcji obiektów ruchomych w czasie rzeczywistym w systemach nadzoru wizyjnego z wykorzystaniem układów FPGA

• Języki publikacji: EN

Abstrakty

EN

The article presents the concept of real-time implementation computing tasks in video surveillance systems. A pipeline implementation of a multimodal background generation algorithm for colour video stream and a moving objects segmentation based on brightness, colour and textural information in reconfigurable resources of FPGA device is described. System architecture, resource usage and segmentation results are presented.

PL

W artykule zaprezentowano koncepcję implementacji zadań obliczeniowych wykorzystywanych w systemach nadzoru wizyjnego w czasie rzeczywistym. Opisano implementację wielomodalnej metody generacji tła dla sekwencji wideo zarejestrowanych w kolorze oraz segmentację obiektów ruchomych z wykorzystaniem informacji o jasności, kolorze i teksturze w zasobach rekonfigurowalnych układów FPGA. Zaprezentowano architekturę systemu, zużycie zasobów i przykładowe rezultaty segmentacji.

Słowa kluczowe

EN

background generation; background subtraction; image processing; hardware acceleration; FPGA

PL

generacja tła; odejmowanie tła; przetwarzanie obrazów; akceleracja sprzętowa; układy FPGA

• Wydawca: Wydawnictwa AGH
• Czasopismo: Computer Science
• Rocznik: 2011
• Tom: Vol. 12
• Strony: 149--162
• Opis fizyczny: Bibliogr. 20 poz., rys., tab.

Twórcy

autor

Kryjak T.

• AGH University of Science and Technology, Faculty of Electrical Engineering, Automatics, IT and Electronics, Department of Computer Science, al. Mickiewicza 30, 30-059 Krakow, Poland

autor

Gorgoń M.

• AGH University of Science and Technology, Faculty of Electrical Engineering, Automatics, IT and Electronics, Department of Computer Science, al. Mickiewicza 30, 30-059 Krakow, Poland

Bibliografia

• [1] Abutaleb M.M., Hamdy A., Abuelwafa M.E., Saad E.M.: FPGA-based object-extraction based on multimodal sigma - delta background estimation. [in:] 2nd International Conference on Computer, Control and Communication, 2009. IC4 2009., Feb. 2009, pp. 1-7.
• [2] Appiah K., Hunter A.: A single-chip FPGA implementation of real-time adaptive background model. [in:] IEEE International Conference on Field-Programmable Technology, 2005. Proceedings., Dec. 2005, pp. 95-102.
• [3] Benedek C., Sziranyi T.: Study on color space selection for detecting cast shadows in video surveillance. Int. J. Imaging Syst. Technol., 17, Oct. 2007, pp. 190-201.
• [4] Butler D., Sridharan S., Bove V. M.Jr.: Real-time adaptive background segmentation. [in:] IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03)., volume 3, vol. 3, Apr. 2003, pages III - 349-52.
• [5] Elgammal A., Harwood D., Davis L.: Non-parametric model for background subtraction. [in:] FRAME-RATE WORKSHOP, IEEE, 2000, pp. 751-767.
• [6] Elhabian S. Y., El-Sayed K. M., Ahmed S. H.: Moving Object Detection in Spatial Domain using Background Removal Techniques - State-of-Art. Recent Patents on Computer Science, 1, 2008, pp. 32-34.
• [7] Gorgon M., Pawlik P., Jablonski M., Przybylo J.: FPGA-based road traffic videodetector. [in:] Proc. of the 10th Euromicro Conference on Digital System Design Architectures, Methods and Tools, Washington, DC, USA, 2007. IEEE Computer Society, pp. 412-419.
• [8] Haritaoglu I., Harwood D., Davis L.S.: W4: Who? when? where? what? a real time system for detecting and tracking people. [in:] Third Face and Gesture Recognition Conference, Apr. 1998, pp. 222-227.
• [9] Jiang H., Ardo H., Owall V.: Hardware accelerator design for video segmentation with multi-modal background modelling. [in:] IEEE International Symposium on Circuits and Systems, 2005. ISCAS 2005., , vol. 2, May. 2005, pp. 1142-1145.
• [10] Juvonen M. P. T., Coutinho J. G. F., Luk W.: Hardware architectures for adaptive background modelling. [in:] 3rd Southern Conference on Programmable Logic, 2007. SPL '07., Feb. 2007, pp. 149-154.
• [11] Kim K., Chalidabhongse T.H., Harwood D., Davis L.: Real-time foreground-background segmentation using codebook model. Real-Time Imaging, 11, Jun. 2005, pp. 172-185.
• [12] Li Q-Z., He D-X., Wang B.: Effective moving objects detection based on clustering background model for video surveillance. [in:] Proc. of the 2008 Congress on Image and Signal Processing, vol. 3, CISP '08, Washington, DC, USA, 2008. IEEE Computer Society, pp. 656-660.
• [13] Makarov A.: Comparison of background extraction based intrusion detection algorithms. [in:] International Conference on Image Proc., 1996. Proc., vol. 1, Sep. 1996, pp. 521-524.
• [14] McFarlane N.J.B., Schofield C.P.: Segmentation and tracking of piglets in images. Machine Vision and Applications, 8, 1995, pp. 187-193. 10.1007/BF01215814.
• [15] Mueller R., Teubner J., Alonso G.: Data processing on FPGAs. [in:] Very Large Data Bases Conference, Lyon, 2009.
• [16] Oliveira J., Printes A., Freire R. C. S., Melcher E., Silva I. S. S.: FPGA architecture for static background subtraction in real time. [in:] Proc. of the 19th annual symposium on Integrated circuits and systems design, SBCCI '06, New York, NY, USA, 2006, pp. 26-31. ACM.
• [17] Qin R., Liao S., Lei Z., Li S.Z.: Moving cast shadow removal based on local descriptors. [in:] 20th International Conference on Pattern Recognition (ICPR), 2010, pages 1377-1380, Aug. 2010.
• [18] Salem M. A. M., Klaus K., Winkler F., Meffert B.: Resolution mosaic-based smart camera for video surveillance. [in:] Third ACM/IEEE International Conference on Distributed Smart Cameras, ICDSC 2009., Sep. 2009, pp. 1-7.
• [19] Stauffer C., Grimson W.E.L.: Adaptive background mixture models for real-time tracking. [in:] IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 1999, volume 2, 1999, pp. (xxiii+637+663).
• [20] Wren C. R., Azarbayejani A., Darrell T., Pentland A. P.: Pfinder: real-time tracking of the human body. IEEE Transactions on Pattern Analysis and Machine Intelligence, 19(7), Jul. 1997, pp. 780-785.