Comparative Analysis of Tracking Objects Using Optical Flow and Background Estimation on Silent Camera
Corresponding Author(s) : Wahyu Supriyatin
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control,
Vol 3, No 2, May-2018
Abstract
Tracking and object is one of the utilizations on the field of the computer vision application. Object tracking utilization as a computer vision in this study is used to identify objects which exist within a frame and calculate the number of objects passing within a frame. The utilization of computer vision in various fields of application can be used to solve the existing problems. The method used in object tracking is by comparison between optical flow estimation method with background method. The test is conducted by using a still camera for both methods by making changes to the parameter values used as a reference. The results of the tests, conducted on the three video objects by comparing the two methods show a Total Recorded Time better than those of the background estimation method, being smaller than 100 seconds. Testing both methods successfully identifies the object tracking and calculates the number of passing cars.
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- W. Supriyatin, and W. W. Ariestya, “Analysis of Object Tracking Using Optical Flow in Static and Moving Camera,” National Seminar of Information Technological (SRITI), Vol. VIII, Pp. 48-56, 2016.
- W. Supriyatin, Y. Rafsyam, and Jonifan, “Analysis of Object Tracking Using Background Estimation in Static and Moving Camera,” Orbith, Vol. 13, No. 2, Ppp. 124-130, 2017.
- A. P. Shukla, and M. Saini, “Moving Object Tracking of Vehicle Detection: A Concise Review,” International Journal of Signal Processing, Image Processing and Pattern Recognition, Vol. 8, No.3, Pp. 169-176, 2015.
- S. K. Singh, and U. Sharma, “Simulink Model for Object Tracking Using Optical Flow,” International Journal of Science and Research (IJSR), Vol. 4, No. 6, Pp. 2323-2326, 2015.
- D. R. Vinary, AND N. L. Kumar, “Object Tracking Using Background Subtraction Algorithm,” International Journal of Engineering Research and General Science, Vol. 3, No. 1, 2015.
- P. D. Mahamuni, R. P. Patil, and H. S. Thakar, “Moving Object Detection Using Background Subtraction Algorithm Using Simulink,” IJRET: International Journal of Research in Engineering and Technology, Vol. 03, No. 06, 2014.
- J. Scott, M. A. Pusateri, and D. Cornish, “Kalman Filter Based Video Background Estimation,”
- S. Aslani, and H. M. Nasab, “Optical Flow Based Moving Object Detection and Tracking for Traffic Surveillance”, International Journal of Electrical, Computer, Energetic, Electronic and Communication Engineering, Vol. 7, No. 9, Pp. 1252-1256, 2013.
- R. Revathi, and M. Hemalatha, “Certain Approach of Object Tracking using Optical Flow Techniques,” International Journal of Computer Applications, Vol. 53, No. 8, Pp. 50-57, 2012.
- M. Himanshu, M. Dubasi, and R. S. Soumya, “Video Object Tracking Using Motion Estimation,” Thesis, Roulkela: Postgraduate of National Institute of Technology, 2012.
- Mahali, M. Izzuddin, and A. Harjoko, “Moving Object Tracking Using Mean-Shift Method Using Scale Orientation Alterations,” Berkala MIPA, Vol. 24, No. 2, 2014.
References
W. Supriyatin, and W. W. Ariestya, “Analysis of Object Tracking Using Optical Flow in Static and Moving Camera,” National Seminar of Information Technological (SRITI), Vol. VIII, Pp. 48-56, 2016.
W. Supriyatin, Y. Rafsyam, and Jonifan, “Analysis of Object Tracking Using Background Estimation in Static and Moving Camera,” Orbith, Vol. 13, No. 2, Ppp. 124-130, 2017.
A. P. Shukla, and M. Saini, “Moving Object Tracking of Vehicle Detection: A Concise Review,” International Journal of Signal Processing, Image Processing and Pattern Recognition, Vol. 8, No.3, Pp. 169-176, 2015.
S. K. Singh, and U. Sharma, “Simulink Model for Object Tracking Using Optical Flow,” International Journal of Science and Research (IJSR), Vol. 4, No. 6, Pp. 2323-2326, 2015.
D. R. Vinary, AND N. L. Kumar, “Object Tracking Using Background Subtraction Algorithm,” International Journal of Engineering Research and General Science, Vol. 3, No. 1, 2015.
P. D. Mahamuni, R. P. Patil, and H. S. Thakar, “Moving Object Detection Using Background Subtraction Algorithm Using Simulink,” IJRET: International Journal of Research in Engineering and Technology, Vol. 03, No. 06, 2014.
J. Scott, M. A. Pusateri, and D. Cornish, “Kalman Filter Based Video Background Estimation,”
S. Aslani, and H. M. Nasab, “Optical Flow Based Moving Object Detection and Tracking for Traffic Surveillance”, International Journal of Electrical, Computer, Energetic, Electronic and Communication Engineering, Vol. 7, No. 9, Pp. 1252-1256, 2013.
R. Revathi, and M. Hemalatha, “Certain Approach of Object Tracking using Optical Flow Techniques,” International Journal of Computer Applications, Vol. 53, No. 8, Pp. 50-57, 2012.
M. Himanshu, M. Dubasi, and R. S. Soumya, “Video Object Tracking Using Motion Estimation,” Thesis, Roulkela: Postgraduate of National Institute of Technology, 2012.
Mahali, M. Izzuddin, and A. Harjoko, “Moving Object Tracking Using Mean-Shift Method Using Scale Orientation Alterations,” Berkala MIPA, Vol. 24, No. 2, 2014.