Abstract
This paper presents an effective method to detect moving objects for videos captured by a moving camera. Moving object detection is relatively difficult to videos captured by a moving camera, since in the case of the video filmed by moving cameras, not only do the objects move, but also the frames shift. In the proposed schemes, the feature points in the frames are first found and then classified into the foreground and background. Next, the foreground regions and image difference are obtained and then further merged to obtain moving object contours. Finally, the moving object is detected based on the motion history of the continuous motion contours and refinement schemes. Experimental results show that the proposed method performs well in terms of moving object detection.
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References
Huang, D.-Y., Chen, C.-H., Hu, W.-C., Yi, S.-C., Lin, Y.-F.: Feature-based Vehicle Flow Analysis and Counting for a Real-Time Traffic Surveillance System. Journal of Information Hiding and Multimedia Signal Processing 3(3), 282–296 (2012)
Dupuis, Y., Savatier, X., Ertaud, J.-Y., Vasseur, P.: Robust Radial Face Detection for Omnidirectional Vision. IEEE Transactions on Image Processing 22(5), 1808–1821 (2013)
Sugandi, B., Kim, H., Tan, J.K., Ishikawa, S.: Real Time Tracking and Identification of Moving Persons by Using a Camera in Outdoor Environment. International Journal of Innovative Computing, Information and Control 5(5), 1179–1188 (2009)
Huang, D.-Y., Lin, T.-W., Hu, W.-C., Cheng, C.-H.: Gait Recognition based on Gabor Wavelets and Modified Gait Energy Image for Human Identification. Journal of Electronic Imaging 22(4), 043039(1)–043039(11) (2013)
Hu, W.-C., Yang, C.-Y., Huang, D.-Y.: Robust Real-time Ship Detection and Tracking for Visual Surveillance of Cage Aquaculture. Journal of Visual Communication and Image Representation 22(6), 543–556 (2011)
Tian, Y.L., Feris, R.S., Haowei, L., Hampapur, A., Sun, M.-T.: Robust Detection of Abandoned and Removed Objects in Complex Surveillance Videos. IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews 41(5), 565–576 (2011)
Lee, D.-S.: Effective Gaussian Mixture Learning for Video Background Subtraction. IEEE Transactions on Pattern Analysis and Machine Intelligence 27(5), 827–832 (2005)
Wang, L., Yung, N.H.C.: Extraction of Moving Objects from their Background based on Multiple Adaptive Thresholds and Boundary Evaluation. IEEE Transactions on Intelligent Transportation Systems 11, 40–51 (2010)
Zhu, S., Guo, Z.: An Overview of Video Object Segmentation. In: Proceedings of International Conference on Industrial Control and Electronics Engineering, pp. 1019–1021 (2012)
Carmona, E.J., MartÃnez-Cantos, J., Mira, J.: A New Video Segmentation Method of Moving Objects based on Blob-level Knowledge. Pattern Recognition Letters 29(3), 272–285 (2008)
Hu, W.-C., Chen, C.-H., Huang, D.-Y., Ye, Y.-T.: Video Object Segmentation in Rainy Situations based on Difference Scheme with Object Structure and Color Analysis. Journal of Visual Communication and Image Representation 23(2), 303–312 (2012)
Jodoin, P.M., Mignotte, M., Rosenberger, C.: Segmentation Framework based on Label Field Fusion. IEEE Transactions on Image Processing 16(10), 2535–2550 (2007)
Wang, Y.: Joint Random Field Model for All-weather Moving Vehicle Detection. IEEE Transactions on Image Processing 19(9), 2491–2501 (2010)
Ghosh, A., Subudhi, B.N., Ghosh, S.: Object Detection from Videos Captured by Moving Camera by Fuzzy Edge Incorporated Markov Random Field and Local Histogram Matching. IEEE Transactions on Circuits and Systems for Video Technology 22(8), 1127–1135 (2012)
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© 2014 Springer International Publishing Switzerland
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Hu, WC., Chen, CH., Chen, CM., Chen, TY. (2014). Effective Moving Object Detection from Videos Captured by a Moving Camera. In: Pan, JS., Snasel, V., Corchado, E., Abraham, A., Wang, SL. (eds) Intelligent Data analysis and its Applications, Volume I. Advances in Intelligent Systems and Computing, vol 297. Springer, Cham. https://doi.org/10.1007/978-3-319-07776-5_36
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DOI: https://doi.org/10.1007/978-3-319-07776-5_36
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-07775-8
Online ISBN: 978-3-319-07776-5
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