Vision Based Tracking of Moving Target in an Autonomous Ground Vehicle Framework
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A. Talukder, L. Matthies. "Real-Time Detection of Moving Objects from Moving Vehicles Using Dense Stereo and Optical Flow". IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2004), Sendai, Japan, 28 September–2 October 2004;Volume 4, pp. 3718–3725.
P.Tissainayagam, D. Suter," Object tracking in image sequences using point features", Pattern Recogn. 2005, 38, pp. 105–113.
A. Milella, R. Siegwart," Stereo-Based Ego-Motion Estimation Using Pixel Tracking and Iterative Closest Point", IEEE International Conference on Computer Vision Systems (ICVS ’06), New York, NY, USA, 5–7 January 2006; pp. 21–21.
M.Leslar, J. Wang, B. Hu, " Comprehensive utilization of temporal and spatial domain outlier detection methods for mobile terrestrial lidar data", Remote Sens. 2011, 3, pp. 1724–1742.
C.H. Huang, Y.T. Wu, J.H. Kao, M.Y. Shih, C.C.Chou, " A Hybrid Moving Object Detection Method for Aerial Images", Advances in Multimedia Information Processing (PCM 2010);
G.Qiu, K. Lam, H. Kiya, X.Y. Xue, C.C. Kuo, M. Lew, Eds.; Lecture Notes in Computer Science; Springer: Berlin/Heidelberg, Germany, 2010; Volume 6297, pp. 357–368.
H. Samija, I. Markovic, I. Petrovic, " Optical Flow Field Segmentation in an Omnidirectional Camera Image Based on Known Camera Motion", 34th International Convention MIPRO, Opatija, Croatia, 23–27 May 2011; pp. 805–809.
N. Suganuma, T. Kubo, Fast Dynamic Object Extraction Using Stereovision Based on Occupancy"Grid Maps and Optical Flow" 2011 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM), Budapest, Hungary, 3–7 July 2011; pp. 978–983.
Z.Jia, A. Balasuriya, S. Challa, "Sensor fusion-based visual target tracking for autonomous"vehicles with the out-of-sequence measurements solution", Robot. Auton. Syst. 2008, 56, pp. 157–176.
J. G. Allen, R. Y. D. Xu and J. S. Jin, "Object tracking using CamShift algorithm and multiple quantized feature spaces", In ACM International Conference Proceeding Series, Vol.100, pp. 3-7, 2004.
D. Comaniciu, P. Meer, Mean shift: a robust approach to feature space analysis, IEEE Transactions on Pattern Analysis and Machine Intelligence 24 (2002) 603.Adaptive Feature Selection and Scale Adaptation", ICIP 2007. IEEE International Conference on Image Processing, 2007.
DOI: http://dx.doi.org/10.21535%2Fijrm.v2i2.134
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