TY - GEN
T1 - Human Sperm tracking using Particle Swarm Optimization combined with Smoothing Stochastic sampling on low frame rate video
AU - Aprinaldi,
AU - Jati, Grafika
AU - Gunawan, Alexander A.S.
AU - Bowolaksono, Anom
AU - Lestari, Silvia Werdhy
AU - Jatmiko, Wisnu
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2016/3/21
Y1 - 2016/3/21
N2 - In this paper, we present a technique for visual tracking in the field of Human Sperm motion. Application of sperm cell tracking is mainly important in Intracytoplasmic Sperm Injection (ICSI), a medical procedure that has enabled the In Vitro Fertilization (IVF) of a single sperm which is injected directly into an egg. In this paper, we consider the problem of tracking single object in video sequences of human sperms and a newly developed Smoothing Stochastic Approximate Monte Carlo (SSAMC) based tracker enhanced by Particle Swarm Optimization (PSO). The problem for this research is that the motility or movement of Human Sperm is fast and unpredictable. In addition, each and every sperms have closely similar size and shape. To solve this problem, we used PSO for searching algorithm (finding the best target) in a Search Window, it can reduce the search space in every each consecutive frame. The measurement results of the proposed method are then compared with the manual measurements done by experts. The experiment results were conducted on both open video data and our own video data. Experiment results showed that the proposed method can handle our specific problem in human sperm cell tracking, and give us a better result as compared to our previous tracker, which used geometric transition dynamic model and without any enhancement by PSO.
AB - In this paper, we present a technique for visual tracking in the field of Human Sperm motion. Application of sperm cell tracking is mainly important in Intracytoplasmic Sperm Injection (ICSI), a medical procedure that has enabled the In Vitro Fertilization (IVF) of a single sperm which is injected directly into an egg. In this paper, we consider the problem of tracking single object in video sequences of human sperms and a newly developed Smoothing Stochastic Approximate Monte Carlo (SSAMC) based tracker enhanced by Particle Swarm Optimization (PSO). The problem for this research is that the motility or movement of Human Sperm is fast and unpredictable. In addition, each and every sperms have closely similar size and shape. To solve this problem, we used PSO for searching algorithm (finding the best target) in a Search Window, it can reduce the search space in every each consecutive frame. The measurement results of the proposed method are then compared with the manual measurements done by experts. The experiment results were conducted on both open video data and our own video data. Experiment results showed that the proposed method can handle our specific problem in human sperm cell tracking, and give us a better result as compared to our previous tracker, which used geometric transition dynamic model and without any enhancement by PSO.
KW - Human Sperm Cell Tracking
KW - PSO
KW - SSAMC
KW - Search Window
UR - http://www.scopus.com/inward/record.url?scp=84966687484&partnerID=8YFLogxK
U2 - 10.1109/MHS.2015.7438308
DO - 10.1109/MHS.2015.7438308
M3 - Conference contribution
AN - SCOPUS:84966687484
T3 - 2015 International Symposium on Micro-NanoMechatronics and Human Science, MHS 2015
BT - 2015 International Symposium on Micro-NanoMechatronics and Human Science, MHS 2015
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - International Symposium on Micro-NanoMechatronics and Human Science, MHS 2015
Y2 - 23 November 2015 through 25 November 2015
ER -