Open Access Open Access  Restricted Access Subscription or Fee Access

Real-Time Moving Objects Tracking for Distributed Smart Video Surveillances

(*) Corresponding author

Authors' affiliations



Tracking the object of interest within a camera's view is essential for crime prevention. This study focuses on analyzing video surveillance in public places. It presents a novel approach to track moving objects across non-overlapping cameras' views that is able to give a consistent label to the objects throughout the whole multi-camera system in real-time. The proposed algorithm is also expected to be able to handle common problems in multiple-camera object tracking including variation of poses, object appearances and occlusion problems. The proposed algorithm was formulated based on visual and temporal cues for multiple cameras using entering/exiting and merging/splitting cases to deal with appearance changes and occlusion problems. Spatial cues are adopted in single-camera object tracking for real-time performance. A novel object segmentation technique based on the observed mask binary value is presented to deal with pose variation across different cameras. In the result section, the comparison between past works and the proposed tracking algorithm are presented. The experimental results show that the algorithm is able to give an optimal trade-off between accuracy and speed.
Copyright © 2016 Praise Worthy Prize - All rights reserved.


Tracking; Non-Overlapping; Visual Cues; Spatial; Temporal

Full Text:



N. Ibrahim, M. M. Mustafa, S. S. Mokri, L. Y. Siong, A. Hussain, Detection of Snatch Theft Based on Temporal Differences in Motion Flow File Oriental Histograms, Proc. Int. Conf. Advancements in Computing Technology (IJACT), 4, 2012, pp. 308–317.

S. Rahimi, A. Aghagolzadeh, H. Seyedarabi, Three Camera-Based Human Tracking Using weighted Colour and Cellular LBP histograms in a Particle Filter Framework, Proc. IEEE 21st Iranian Conf. Electrical Engineering (ICEE), Mashhad, 2013, pp. 1–6.

L. Zhang, H. Dibeklio˘glu, L.J.P. van der Maaten, Speeding Up Tracking by Ignoring Features, Proc. IEEE IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Columbus, OH, 2014, pp. 1266–1273.

Y. Cai, K. Huang, T. Tan, Matching tracking sequences across widely separated cameras, Proc. IEEE 15th Int. Conf. Image Processing (ICIP 2008), San Diego, CA, 2008, pp. 765–768.

Q. Huang, J. Yang, Y. Qiao, Person re-identification across multi-camera system based on local descriptors, Proc. IEEE in Sixth Int. Conf. on Distributed Smart Cameras (ICDSC), 2012, pp. 1–6.

M. Danelljan, F. S. Khan, M. Felsberg, J. van der Weijer, Adaptive Colour Attributes for Real-Time Visual Tracking, Proc. IEEE Conf. on Computer Vision and Pattern Recognition, Columbus, OH, 2014, pp. 1090–1097.

J. Xu, V. Jagadeesh, Z. Ni, S. Sunderrajan, B. S. Manjunath, Graph-based topic-focused retrieval in distributed camera network, (2013) IEEE Transactions on Multimedia, 15 (8), pp. 1–13.

D. T. Lin, K. Y. Huang, Collaborative Pedestrian Tracking and Data Fusion with Multiple Cameras, (2011) IEEE Trans. Inf. Forens. Security, 6 (4), pp. 1432–1444.

R. Zhang, J. Ding, Object Tracking and Detecting Based on Adaptive Background Subtraction, (2012) Procedia Engineering, 29, pp. 1351–1355.

Y. Yang, Z. Wang, D. Sun, M. Zhang, N. Cheng, Automatic Object Tracking Using Edge Orientation Histogram Based CamShift, in Proc. IEEE Third Int. Conf. on Information and Computing (ICIC), Wuxi, Jiang Su, 2010, pp. 231–234.

M. O. Mehmood, A. Khawaja, Multi-camera based human tracking with non-overlapping fields of view, Proc. IEEE 5th Int. Conf. Image and Graphics, Xi'an, Shanxi, 2009, pp. 313–318.

C. Stauffer, W. Grimson, Adaptive background mixture models for real-time tracking, IEEE Computer Conference on Computer Vision and Pattern Recognition, vol. 2, 1999, pp. 2246–2252.

J. Sherrah, D. Kamenetsky, T. Scoleri, Evaluation of similarity measures for appearance-based multi-camera matching, Fifth ACM/IEEE Int. Conf. on Distributed Smart Cameras (ICDSC), Ghent, 2011, pp. 1–6.

Hdioud, B., Tirari, M., Thami, R., Video Surveillance: Analyzing People’s Movements in a Closed Environment, (2014) International Review on Computers and Software (IRECOS), 9 (3), pp. 495-501.

D. Jansari, S. Parmar, G. Saha, Real-Time Object Tracking Using Colour-Based Probability Matching, Proc. Int. Conf. on Signal Processing, Computing and Control (ISPCC), Solan, 2013, pp. 1–6.

Y. Wang, L. He, S. Velipasalar, Real-time distributed tracking with non-overlapping cameras, Proc. IEEE 17th Int. Conf. Image Processing, Hong Kong, 2010, pp. 697–700.

H. H. Hsu, W. M. Yang, T. K. Shih, People Tracking in a Multi-Camera Environment, Proc. IEEE Conf. Anthology, China, 2013, pp. 1–4.

Y. Wang, S. Velipasalar, M. C. Gursoy, Wide-area multi-object tracking with non-overlapping camera views, Proc. IEEE International Conference on Multimedia and Expo (ICME), China, 2013, pp. 1–4.

Q. Zhou, J. K., Aggarwal, Object tracking in an outdoor environment using fusion of features and cameras, (2006) Image and Vision Computing, 24 (11), pp. 1244–1255.

Ait Ali, M., Zhar, N., Berrahou, A., Eleuldj, M., Parallel Implementation of a Blob Detection Algorithm on FPGA, (2014) International Review on Computers and Software (IRECOS), 9 (12), pp. 2001-2008.

H. Wang, D. Suter, K. Schindler, Effective Appearance Model and Similarity Measure for Particle Filtering and Visual Tracking, (2006) Computer Vision-ECCV 2006, 3953, pp. 606–618.

C. Sachdeva, R. Biro, Real Time Object Tracking Using Different Mean Shift Techniques–a Review, (2013) International Journal of Soft Computing and Engineering (IJSCE), pp. 98–102.

A. Pathak, E. Singh, Comparative Study on Filtering Techniques of Digital Image Processing, (2014) Advance in Electronic and Electric Engineering, 4 (6), pp. 669–674.

X. Chen, K. Huang, T. Tan, Object tracking across non-overlapping cameras using adaptive models, Proceedings of Asian Conference on Computer Vision Workshops, 2012, pp.464–477.

X. Chen, K. Huang, T. Tan, Object tracking across non-overlapping views by learning inter-camera transfer models, (2014) Pattern Recognition, 47 (3), pp. 1126-1137.

M. Huang, G. Chen, G.-f. Yang, R. Cao, An Algorithm of the Target Detection and Tracking of the Video, (2012) Procedia Engineering, 29, pp. 2567–2571.

M. Sonka, V. Hlavac, R. Boyle, Image Processing, Analysis, and Machine Vision (3rd ed.), (Thomson, 2008, 11-557).

A. M. Ibrahim, Automated Tracking System for Video Surveillance System, Master thesis, Dept. Mechatronics Eng., International Islamic University Malaysia, 2013.

N. N. A. Aziz, Y. M. Mustafah, A.W. Azman, N. A. Zainuddin, M. A. Rashidan, Features Selection for Multi-camera Tracking, IEEE Int. Conf. Computer and Communication Engineering (ICCCE), Kuala Lumpur, 2014, pp. 243–246.

N. N. A. Aziz, Y. M. Mustafah, A. A. Shafie, M. A. Rashidan, N. A. Zainuddin, Real-Time Tracking using Edge and Colour Feature, IEEE Int. Conf. Computer and Communication Engineering (ICCCE), Kuala Lumpur, 2014, pp. 247–250.

A. Senior, A. Hampapur, Y. L. Tian, L. Brown, S. Pankanti, R. Bolle, Appearance models for occlusion handling, (2006) Image and Vision Computing, 24 (11), pp. 1233–1243.

H. Sabirin, M. Kim, Moving Object Detection and Tracking using a Spatio-Temporal Graph in H.264/AVC Bitstreams for Video Surveillance, (2012) IEEE Transactions on Multimedia, 14 (3), pp. 657-668.

S. Zhang, S. C. Chan, R. D. Qiu, K. T. Ng, Y. S. Hung, W. Lu, On the Design and Implementationof a high Definition Multiview Intelligent Video Surveillance System, Proc. IEEE 5th Int. Conf. Signal Processing, Communication and Computing (ICSPCC), Hong Kong, 2012, pp. 353–35.

X. Chen, K. Huang, T. Tan, Direction-based Stochastic Matching for Pedestrian Recognition in Non-overlapping Cameras, 18th IEEE International Conference on Image Processing, 2011, pp. 2065-700.

PETS2001 Dataset 1 Camera 1, Retrieved March 18, 2015.

Dataset for Two Non-overlapping Cameras, Retrieved March 6, 2015.

Three-camera network with non-overlapping views (Dataset 1 Camera 2 and Camera 3), Retrieved July 17, 2014.

Dataset for Three-camera network with non-overlapping views, Retrieved December 18, 2014.

C. Zhao, Q. Pan, S. Z. Li, Real time people tracking and counting in visual surveillance, The Sixth World Congress on Intelligent Control and Automation, WCICA 2006, vol. 2, 2006, pp. 9722-9724.


  • There are currently no refbacks.

Please send any question about this web site to
Copyright © 2005-2023 Praise Worthy Prize