Visual Object Target Tracking Using Particle Filter: A Survey

Автор: G.Mallikarjuna Rao, Ch.Satyanarayana

Журнал: International Journal of Image, Graphics and Signal Processing(IJIGSP) @ijigsp

Статья в выпуске: 6 vol.5, 2013 года.

Бесплатный доступ

This paper gives the survey of the existing developments of Visual object target tracking using particle filter from the last decade and discusses the advantage and disadvantages of various particle filters. A variety of different approaches and algorithms have been proposed in literature. At present most of the work in Visual Object Target Tracking is focusing on using particle filter. The particle filters has the advantage that they deal with nonlinear models and non-Gaussian innovations, and they focus sequentially on the higher density regions of the state space, mostly parallelizable and easy to implement, so it gives a robust tracking framework, as it models the uncertainty and showing good improvement in the recognition performance compared to the kalman filter and other filters like Extended Kalman Filter (EKF), Unscented Kalman Filter (UKF).Various features and classifiers that are used with particle filter are given in this survey.

Еще

Kalman Filter, Extended Kalman Filter, Unscented Kalman Filter, Particle Filter, Visual Object Tracking

Короткий адрес: https://sciup.org/15012883

IDR: 15012883

Список литературы Visual Object Target Tracking Using Particle Filter: A Survey

M. S. A. Yilmaz, O. Javed, "'Object tracking: A survey'," ACM Computing Surveys, vol. 38, no. 4, 2006.
G. Quesnel, H. Raynal, E. Ramat, and D. Makowski, "Software environments for implementing the particle filter with dynamic models," pp. 2001–2002, 2006.
Bishop and Welch, "An Introduction to the Kalman Filter". 2001.
http://en.wikipedia.org/wiki/Kalman_filter
http://www.cs.bilkent.edu.tr/~ismaila/MUSCLE/MSTracker.htm
A. Yilmaz and O. Javed, "Object Tracking : A Survey," ACM Computing Surveys, vol. 38, no. 4, pp. 1–45, 2006.
Z. B. Musa and J. Watada, "Motion Tracking Using Particle Filter," Lecture Notes in Artificial Intellegence, pp. 119–126, 2008.
H. Pistori, "Mice and larvae tracking using a particle filter with an auto-adjustable observation model," Pattern Recognition Letters, vol. 31, no. 4, pp. 337–346, 2010.
D. Forte and A. Srivastava, "Resource-Aware Architectures for Particle Filter Based Visual Target Tracking," 2011.
P. Chen and H. Q. W. W. M. Zhu, "Contour tracking using Gaussian particle filter," IET Image Processing, vol. 5, no. June 2009, pp. 440–447, 2011.
A. Carmi and L. Mihaylova, "Markov Chain Monte Carlo Particle Algorithms for Discrete-Time Nonlinear Filtering," Monte Carlo Methods Appl, pp. 1–10.
D. Simon, Optimal State Estimation: Kalman, H Infinity, and Nonlinear Approaches. pp. 1–530.
H. Liu and F. Sun, "Efficient visual tracking using particle filter with incremental likelihood calculation," Information Sciences, vol. 195, pp. 141–153, 2012.
B. Zhang, W. Tian, and Z. Jin, "Joint tracking algorithm using particle filter and mean shift with target model updating," Chinese Optics Letters, vol. 4, no. 10, pp. 4–7, 2006.
B. N. Bevilacqua, "Tutorial: Rao-Blackwell Particle Filtering."
W. Qi, X. Zhang, L. Chao, O. Yuanxin, and S. Hao, "A Robust approach for multiple vehicles tracking using layered particle filter," AEUE - International Journal of Electronics and Communications, vol. 65, no. 7, pp. 609–618, 2011.
Z. H. E. Chen, "Bayesian Filtering : From Kalman Filters to Particle Filters , and Beyond VI Sequential Monte Carlo Estimation : Particle Filters," 2003.
N. G. Branko Ristic, Sanjeev Arulampalam, Beyond the Kalman Filter: Particle Filters for Tracking Applications. Artech House, 2003.
S. Simo, "TIME-VARYING SYSTEMS : Discrete-Time Systems," vol. 2, no. C, pp. 2009–2011, 2011.
M. Milelli, A. P. Printed, and D. Wetterdienst, "Is the particle Filtering Approach Appropriate for Meso-Scale Data Assimiltion."
C. Kreucher, A. O. Hero, K. Kastella, B. Avenue, A. Arbor, P. O. Box, and A. Arbor, "MULTIPLE MODEL PARTICLE FILTERING FOR MULTI-TARGET TRACKING," pp. 1–6, 2004.
http://en.wikipedia.org/wiki/Auxiliary_particle_filter
M. Pitt and N. Shephard, "Filtering via simulation: Auxiliary particle filters," Journal of the American statistical …, vol. 94, no. 446, pp. 590–599, 1999.
D. Wang, Q. Zhang, and J. Morris, "Distributed Markov Chain Monte Carlo kernel based particle filtering for object tracking," Multimedia Tools and Applications, vol. 56, no. 2, pp. 303–314, Nov. 2010.
R. Chen and J. S. Liu, "Mixture Kalman Filters 1 Introduction," no. 1960, pp. 1–26.
Y. Rui and Y. Chen, "Better proposal distributions: object tracking using unscented particle filter," Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001, vol. 2, no. 1, pp. II–786–II–793.
A. T. Submitted, I. N. Partial, F. Of, T. H. E. Requirements, F. O. R. The, and D. Of, "Robust Visual Tracking for Multiple Targets," 2005.
K. Nummiaro, E. Koller-Meier, and L. Van Gool, "Object tracking with an adaptive color-based particle filter," Pattern Recognition, pp. 353–360, 2002.
J. Ma, C. Han, and Y. Chen, "Efficient visual tracking using particle filter," Information Fusion, 2007 .
P. Li, T. Zhang, and A. E. C. Pece, "Visual contour tracking based on particle filters," vol. 21, pp. 111–123, 2003.
C. Engineering, M. Seminar, and H. Azimian, "Visual Object Tracking Algorithms," 2005.
A. Li, Z. Jing, and S. Hu, "Particle filter based visual tracking with multi-cue adaptive fusion," Chinese Optics Letters, vol. vol 3, 2005.
X. Xu and B. Li, "Rao-Blackwellised particle filter for tracking with application in visual surveillance," Tracking and Surveillance, 2005..
P. Vadakkepat and L. Jing, "Improved Particle Filter in Sensor Fusion for Tracking Randomly Moving Object," IEEE Transactions on Instrumentation and Measurement, vol. 55, no. 5, pp. 1823–1832, 2006.
F. L. Lim, W. Leoputra, and T. Tan, "Non-overlapping Distributed Tracking System Utilizing Particle Filter," Journal of VLSI Signal Processing, vol. 49, pp. 343–362, 2007.
R. Mottaghi and R. Vaughan, "An integrated particle filter and potential field method applied to cooperative multi-robot target tracking," Auton Robot, vol. 23, pp. 19–35, 2007.
G. U. O. Rong-hua and Q. I. N. Zheng, "An unscented particle filter for ground maneuvering target tracking," Journal of Zhejiang University SCIENCE A, vol. 8, no. 10, pp. 1588–1595, 2007.
C. Shan, T. Tan, and Y. Wei, "Real-time hand tracking using a mean shift embedded particle filter," Pattern Recognition, vol. 40, pp. 1958–1970, 2007.
S. Sa, "Rao-Blackwellized particle filter for multiple target tracking," Information Fusion, vol. 8, pp. 2–15, 2007.
J. Czyz, B. Ristic, and B. Macq, "A particle filter for joint detection and tracking of color objects," Image and Vision Computing, vol. 25, pp. 1271–1281, 2007.
J. Li and C. Chua, "Transductive local exploration particle filter for object tracking," Image and Vision Computing, vol. 25, pp. 544–552, 2007.
A. Li, Z. Jing, and S. Hu, "Robust observation model for visual tracking in particle filter," AEU-International Journal of Electronics and …, vol. 61, pp. 186–194, 2007.
A. S. Montemayor, A. Duarte, J. J. Pantrigo, and A. Sa, "Multi-dimensional visual tracking using scatter search particle filter," Pattern Recognition Letters, vol. 29, pp. 1160–1174, 2008.
S. Choi and D. Kim, "Robust head tracking using 3D ellipsoidal head model in particle filter," Pattern Recognition, vol. 41, pp. 2901–2915, 2008.
B. Zhang, W. Tian, and Z. Jin, "Robust appearance-guided particle filter for object tracking with occlusion analysis," International Journal of Electron. Commun., vol. 62, pp. 24–32, 2008.
P. Taylor, J. Ortegon-aguilar, and E. Bayro-corrochano, "Particle filter tracking without dynamics," Applied Bionics , pp. 37–41, 2008.
B. Guo and W. Sun, "Multiple object detection and tracking with pseudo-particle filter," Front. Electr. Electron. Eng. China, vol. 4, no. 2, pp. 115–120, 2009.
B. Sugandi, H. Kim, and J. Kooi, "A moving object tracking based on color information employing a particle filter algorithm," International Symposium on Artif icial Life and Robotics, pp. 39–42, 2009.
Z. Wang, X. Yang, Y. Xu, and S. Yu, "CamShift guided particle filter for visual tracking," Pattern Recognition Letters, vol. 30, no. 4, pp. 407–413, 2009.
W. Zheng and S. Bhandarkar, "Face detection and tracking using a Boosted Adaptive Particle Filter," Journal of Visual Communication and Image …, vol. 20, no. 1, pp. 9–27, 2009.
W. Lu, K. Okuma, and J. J. Little, "Tracking and recognizing actions of multiple hockey players using the boosted particle filter," Image and Vision Computing, vol. 27, no. 1–2, pp. 189–205, 2009.
C. Liu, P. Liu, J. Liu, and J. Huang, "2D Articulated Pose Tracking Using Particle Filter with Partitioned Sampling and Model Constraints," Journal of Intell Robot Syst, pp. 109–124, 2010.
B. Sugandi, H. Kim, and J. Koi, "A color-based particle filter for multiple object tracking in an outdoor environment," International Symposium on Artif icial Life and Robotics, pp. 41–47, 2010.
S. Ling, Z. Kadim, K. Meng, and M. Kuan, "Hybrid Blob and Particle Filter Tracking Approach for Robust Object Tracking," Procedia Computer Science, vol. 1, no. 1, pp. 2549–2557, 2010.
I. Chang and S. Lin, "3D human motion tracking based on a progressive particle filter," Pattern Recognition, vol. 43, no. 10, pp. 3621–3635, 2010.
X. Wang and Z. Tang, "Modified particle filter-based infrared pedestrian tracking," Infrared Physics and Technology, vol. 53, no. 4, pp. 280–287, 2010.
J. Zhao and Z. Li, "Particle filter based on Particle Swarm Optimization resampling for vision tracking," Expert Systems With Applications, vol. 37, no. 12, pp. 8910–8914, 2010.
L. Jing and P. Vadakkepat, "Interacting MCMC particle filter for tracking maneuvering target," Digital Signal Processing, vol. 20, no. 2, pp. 561–574, 2010.
H. Medeiros, G. Holguín, P. J. Shin, and J. Park, "A parallel histogram-based particle filter for object tracking on SIMD-based smart cameras," Computer Vision and Image Understanding, vol. 114, no. 11, pp. 1264–1272, 2010.
F. Ababsa, "Real-time camera tracking for structured environment using an iterated particle filter," Systems Man and Cybernetics (SMC), 2010 IEEEConference, pp. 3039–3044, 2010.
C.M. Md.ZAHIDUL ISLAM and C.W. L. OH, "An Efficient Multiple Cues Cynthesis for Human Tracking using a Particle Filtering Framework," International Journal of Innovative Computing,Information and Control, vol. 7, no. 6, pp. 3379–3393, 2011.
Z. L. Husz, A. M. Wallace, and P. R. Green, "Tracking With a Hierarchical Partitioned Particle Filter and Movement Modelling," IEEE Transactions On Systems,Man, And Cybernetics, vol. 41, no. 6, pp. 1571–1584, 2011.
K. Qian, X. Ma, X. Dai, and F. Fang, "Improved Rao-Blackwellized particle filter for simultaneous robot localization and person-tracking with single mobile sensor," Journal of Control Theory Applications, vol. 9, no. June 2009, pp. 472–478, 2011.
Z. Hasan, K. Irene, and A. G. Backhouse, "A Robust Particle Filter-Based Method for Tracking Single Visual Object Through Complex Scenes Using Dynamical Object Shape and Appearance Similarity," Journal of Signa Processing Systems, pp. 63–79, 2011.
R. Péteri, "Tracking dynamic textures using a particle filter driven by intrinsic motion information," Machine Vision and Applications, vol. 22, pp. 781–789, 2011.
A. Ortiz, J. Antich, and G. Oliver, "A particle filter-based approach for tracking undersea narrow telecommunication cables," Machine Vision and Applications, vol. 22, pp. 283–302, 2011.
J. Martínez-del-rincón, C. Orrite, and C. Medrano, "Rao – Blackwellised particle filter for colour-based tracking," Pattern Recognition Letters, vol. 32, pp. 210–220, 2011.
L. Raskin, M. Rudzsky, and E. Rivlin, "Dimensionality reduction using a Gaussian Process Annealed Particle Filter for tracking and classification of articulated body motions," Computer Vision and Image Understanding, vol. 115, no. 4, pp. 503–519, 2011.
H. Han, Y. Ding, K. Hao, and X. Liang, "An evolutionary particle filter with the immune genetic algorithm for intelligent video target tracking," Computers and Mathematics with Applications, vol. 62, no. 7, pp. 2685–2695, 2011.
J. Jose and A. S. Montemayor, "Heuristic particle filter: applying abstraction techniques to the design of visual tracking algorithms," Expert Systems, vol. 28, no. 1, pp. 49–69, 2011.
H. Kubota, M. Takeshi, and H. Saito, "3D head pose tracking using a particle filter with nose template matching," Electronics and Communications in Japan, vol. 94, no. 1, pp. 1447–1454, 2011.
R. Cabido, A. S. Montemayor, and J. J. Pantrigo, "High performance memetic algorithm particle filter for multiple object tracking on modern GPUs," Soft Computing, vol. 16, no. 2, pp. 217–230, May 2011.
R. Paper, C. Songxiao, W. Xuanyin, and X. Ke, "Visual Object Servo Tracking Based on the Particle Filter Method Using a Pan-Tilt-Zoom Camera," International Journal of Advanced Robotic Systems, vol. 9, 2012.
D. T. Cong, F. Septier, C. Garnier, L. Khoudour, and Y. Delignon, "Robust Visual Tracking Via Mcmc-Based Particle Filtering," IEEE International Conference on Acoustics, Speech and Signal Processing, Kyoto : Japan, pp. 2–5, 2012.
M. Sun and C. Shi, "Application of particle filtering in visual tracking," Advanced Materials Research, vol. 485, pp. 207–212, 2012.
J. A. Brown, D. W. Capson, and S. Member, "A Framework for 3D Model-Based Visual Tracking Using a GPU-Accelerated Particle Filter," Ieee Transactions On Visualization And Computer Graphics, vol. 18, no. 1, pp. 68–80, 2012.
N. V. Samarjit Das, Amit Kale, "Particle FilterWith a Mode Tracker for Visual Tracking Across Illumination Changes," Ieee Transactions On Image Processing, vol. 21, no. 4, pp. 2340–2346, 2012.
I. Introduction, "An Optimization-Based Parallel Particle Filter for Multitarget Tracking," Ieee
Transactions On Aerospace And Electronic Systems, vol. 48, no. 2, pp. 1601–1618, 2012.
P. Li, "An Efficient Particle Filter – based Tracking Method Using Graphics Processing Unit ( GPU )," Journal of Signa Processing Systems, pp. 317–332, 2012.
M. Ho, C. Chiang, and Y. Su, "Object tracking by exploiting adaptive region-wise linear subspace representations and adaptive templates in an iterative particle filter," Pattern Recognition Letters, vol. 33, no. 5, pp. 500–512, 2012.
Y. C. S. Huang and L. F. P. Hsiao, "Vehicle detection and tracking under various lighting conditions using a particle filter," IET Intelligent Transport Systems, no. May 2011, pp. 1–8, 2012.
H. A. A. El-halym, I. I. Mahmoud, and S. E. D. Habib, "Proposed hardware architectures of particle filter for object tracking," EURASIP Journal on Advances in Signal Processing, pp. 1–19, 2012.
W. Wang and B. Wang, "Feature-driven motion model-based particle-filter tracking method with abrupt motion handling," Optical Engineering, no. 51, p. 4, 2012.

Еще

Статья научная