Detection of Human Movement Direction Using Optical Flow Analisys on Multiple Camera Angles
Main Article Content
Keywords
Abstract
The active movement of children poses a safety risk in the absence of adult supervision. To reduce the risk of accidents in children, an automatic detection system for the direction of children's movements is crucially needed. In this study, detection of the direction of human movement based on image processing was carried out with the input of videos produce from 4 CCTV installed in each corner of the room. The system will detect the direction of object movement with classification of orientation, namely front, back, right and left. The detection method used in this research is Optical Flow. Optical Flow will calculate the value of the direction or orientation of the movement of an object. The orientation obtained is then accumulated with HOOF (Histogram Orientation of Optical Flow), where HOOF will collect the orientation of objects on the whole frame according to a 8-part Cartesian angle. The results of the orientation with Optical Flow will be compared with the direction of detection measured manually to determine whether the detection of movement direction using Optical Flow is running well. According to the results, it is known that the Optical Flow method has succeeded in detecting the direction of movement accurately based on different camera angles.
Keywords : Image Processing, CCTV, Optical Flow, HOOF
References
Windiarto and Yanto, “PROFIL ANAK INDONESIA,” Kementeri. Pemberdaya. Peremp. dan Perlindungan Anak ii, vol. 5, no. 1, pp. 12–21, 2018.
K. Lertniphonphan, S. Aramvith, and T. H. Chalidabhongse, “Human action recognition using direction histograms of optical flow,” 11th Int. Symp. Commun. Inf. Technol. Isc. 2011, vol. c, no. Iscit, pp. 574–579, 2011.
Q. Wu, J. Yang, and J. Wu, “Evaluation of human pointing movement characteristics for improvement of human computer interface,” 2010 IEEE Int. Conf. Inf. Autom. ICIA 2010, pp. 799–804, 2010.
N. Yodpijit, K. Pongmit, T. Sittiwanchai, and M. Jongprasithporn, “Designing a 3D human movement analysis system,” 2017 IEEE 3rd Int. Conf. Eng. Technol. Soc. Sci. ICETSS 2017, vol. 2018-January, pp. 1–5, 2018.
G. Mokhtari, Q. Zhang, and M. Karunanithi, “Modeling of human movement monitoring using Bluetooth Low Energy technology,” Proc. Annu. Int. Conf. IEEE Eng. Med. Biol. Soc. EMBS, vol. 2015-November, pp. 5066–5069, 2015.
M. B. Frasetyo, J. T. Elektro, F. T. Industri, and U. I. Indonesia, “Sistem pendeteksi jatuh pada manusia berbasis pengolahan citra,” 2018.
A. Heinrich, D. Geng, D. Znamenskiy, J. P. Vink, and G. De Haan, “Robust and sensitive video motion detection for sleep analysis,” IEEE J. Biomed. Heal. Informatics, vol. 18, no. 3, pp. 790–798, 2014.
A. Zarkasi et al., “Face Movement Detection Using Template Matching,” Proc. 2018 Int. Conf. Electr. Eng. Comput. Sci. ICECOS 2018, vol. 17, pp. 333–338, 2019.
N. Rawat, J. S. Sodhi, and R. K. Tyagi, “Acquiring and Analyzing Movement Detection through Image Granulation,” IEEE Int. Conf. Issues Challenges Intell. Comput. Tech. ICICT 2019, 2019.
I. V. Paputungan, M. R. Al Fitri, and U. Y. Oktiawati, “Motion and Movement Detection for DIY Home Security System,” 2019 IEEE Conf. Sustain. Util. Dev. Eng. Technol. CSUDET 2019, pp. 122–125, 2019.
S. S. Mane and A. R. Surve, “Engagement detection using video-based estimation of head movement,” 2018 3rd IEEE Int. Conf. Recent Trends Electron. Inf. Commun. Technol. RTEICT 2018 - Proc., pp. 1745–1749, 2018.
A. Solichin, A. Harjoko, and A. E. Putra, “Movement direction estimation on video using optical flow analysis on multiple frames,” Int. J. Adv. Comput. Sci. Appl., vol. 9, no. 6, pp. 174–181, 2018.
M. B. Frasetyo,“Sistem pendeteksi jatuh pada manusia berbasis pengolahan citra,”. Skripsi, tidak diterbitkan, J. T. Elektro, F. T. Industri, and U. I. Indonesia, 2018.
Y. Mi, P. K. Bipin, and R. K. Shah, “Using Lucas-Kanade Algorithms to Measure Human Movement,” Commun. Comput. Inf. Sci., vol. 835, no. 1, pp. 118–130, 2019.
N. Sharmin and R. Brad, “Optimal filter estimation for Lucas-Kanade optical flow,” Sensors (Switzerland), vol. 12, no. 9, pp. 12694–12709, 2012.
R. V. H. M. Colque, C. Caetano, M. T. L. De Andrade, and W. R. Schwartz, “Histograms of Optical Flow Orientation and Magnitude and Entropy to Detect Anomalous Events in Videos,” IEEE Trans. Circuits Syst. Video Technol., vol. 27, no. 3, pp. 673–682, 2017.
Z. Wang, L. Zheng, Y. Liu, and S. Wang, “Towards Real-Time Multi-Object Tracking,” Comput. Sci., vol. 1, pp. 1–9, 2019.
H. Vazirani, A. Kautsar, J. Fisika, F. Sains, and U. Diponegoro, “Implementasi Object Tracking Untuk Mendeteksi Dan Menghitung Jumlah Kendaraan Secara Otomatis Menggunakan Metode Kalman Filter Dan Gaussian Mixture Model,” Youngster Phys. J., vol. 5, no. 1, pp. 13–20, 2016.
S. Usmankhujaev, S. Baydadaev, and K. J. Woo, “Real-time, deep learning basedwrong direction detection,” Appl. Sci., vol. 10, no. 7, pp. 1–13, 2020.
Article Sidebar
Article Details
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).
The authors declare that:
1. This paper has not been published in the same form elsewhere.
2. It will not be submitted anywhere else for publication prior to acceptance/rejection by this Journal.
3. A copyright permission is obtained for materials published elsewhere and which require this permission for reproduction.