TY - GEN
T1 - Multi-sperm tracking using Hungarian Kalman Filter on low frame rate video
AU - Jati, Grafika
AU - Gunawan, Alexander A.S.
AU - Lestari, Silvia Werdhy
AU - Jatmiko, Wisnu
AU - Hilman, M. H.
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2017/3/6
Y1 - 2017/3/6
N2 - One factor of human sperm health is sperm motility. Motility is the ability of sperm to move. Sperm with healthy motility move forward promptly, not inactive and not moving in circles. In this paper, we would like to analyse sperm motility by considering the problem of multi object tracking in video sequences of human sperms. The challenges in multi-sperm tracking are many human sperms have fast and unpredictable movement In addition, the sperm have similar size and shape comparing by each others. To solve this problem, we used sperm detection in each video sequence to get the position of sperms. In the same time, the estimated sperm position is calculated based on previous tracking by using Kalman Filter. Finally the positions of detected sperms are compared to estimation results by using Hungarian assignment method. In this way, the trajectory of each sperm can be conclude. This paper analyze sperm motility qualitatively based on the resulted sperm trajectories. The experiment results were conducted on both open video data and our own low-frame-rate video data. The experiment results shows that the proposed method can handle the challenges in multi sperm tracking, create their trajectory and then analyze their behaviors.
AB - One factor of human sperm health is sperm motility. Motility is the ability of sperm to move. Sperm with healthy motility move forward promptly, not inactive and not moving in circles. In this paper, we would like to analyse sperm motility by considering the problem of multi object tracking in video sequences of human sperms. The challenges in multi-sperm tracking are many human sperms have fast and unpredictable movement In addition, the sperm have similar size and shape comparing by each others. To solve this problem, we used sperm detection in each video sequence to get the position of sperms. In the same time, the estimated sperm position is calculated based on previous tracking by using Kalman Filter. Finally the positions of detected sperms are compared to estimation results by using Hungarian assignment method. In this way, the trajectory of each sperm can be conclude. This paper analyze sperm motility qualitatively based on the resulted sperm trajectories. The experiment results were conducted on both open video data and our own low-frame-rate video data. The experiment results shows that the proposed method can handle the challenges in multi sperm tracking, create their trajectory and then analyze their behaviors.
UR - http://www.scopus.com/inward/record.url?scp=85016991030&partnerID=8YFLogxK
U2 - 10.1109/ICACSIS.2016.7872796
DO - 10.1109/ICACSIS.2016.7872796
M3 - Conference contribution
AN - SCOPUS:85016991030
T3 - 2016 International Conference on Advanced Computer Science and Information Systems, ICACSIS 2016
SP - 530
EP - 535
BT - 2016 International Conference on Advanced Computer Science and Information Systems, ICACSIS 2016
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 8th International Conference on Advanced Computer Science and Information Systems, ICACSIS 2016
Y2 - 15 October 2016 through 16 October 2016
ER -