Abstract
Research in object tracking has become a popular research domain among researchers. The use of video cameras to capture motion images instead of static images poses a great challenge to researchers in terms of speed and accuracy of the object tracking and detection. In this paper, fish are used in the experiment due to its active swimming behaviour which emulates the movement of many living objects such as humans or animals. The main problem faced in the tracking process is that the fishes swim in various directions and angles. It is difficult to track and identify a specific fish in a school of fish in most cases. Besides, the fish may also appear to be overlapping one another. There exists several object tracking systems in the market but the focuses are mainly on surveillance. Besides, there is still room for improvement in the tracking process. Therefore, this paper focuses on using an additional camera for tracking fish in real-time environment. The evaluation of the tracking process consists of using the same video with an additional camera positioned above the fish tank. Results show improvement when an additional camera is used to obtain additional information mainly the trajectory patterns of the fish which contributes to bringing a higher accuracy of the tracking system.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Jia-Hong, L., Mei-Yi, W., Zhi-Cheng, G.: A tank fish recognition and tracking system using computer vision techniques. In: International Conference on Computer Science and Information Technology (ICCSIT), vol. 4, pp. 528–532. IEEE (2010)
Shao, L., Xie, G.: Real-time tracking of moving objects on a water surface. In: International Conference on Mechatronics and Automation (ICMA), pp. 2114–2119. IEEE (2012)
Chew, B.F., Eng, H.L., Thida, M.: Vision-based real-time monitoring on the behavior of fish school. In: IAPR Conference on Machine Vision Applications, pp. 90–93. IEEE (2009)
Wong, P.L., Osman, M.A., Talib, A.Z., Yahya, K.: Modelling of fish swimming patterns using an enhanced object tracking algorithm. In: Sambath, S., Zhu, E. (eds.) Frontiers in Computer Education. AISC, vol. 133, pp. 585–592. Springer, Heidelberg (2012)
Wong, P.L., Osman, M.A., Talib, A., Yahya, K.: Tracking multiple fishes using colour changes identification and enhanced object tracking algorithm. Appl. Mech. Mater. 284–287(1662–7482), 1528–1532 (2013)
Wong, P.L., Osman, M.A., Talib, A.Z., Ogier, J.-M., Yahya, K.: Tracking multiple fish in a single tank using an improved particle filter. In: Jeong, H.Y., Obaidat, M.S., Yen, N.Y., Park, J.J. (eds.) Advances in Computer Science and its Applications. LNEE, vol. 279, pp. 799–804. Springer, Heidelberg (2014)
Meng-Che, C., Jenq-Neng, H., Williams, K., Towler, R.: Multiple fish tracking via Viterbi data association for low-frame-rate underwater camera systems. In: International Symposium on Circuits and Systems (ISCAS), pp. 2400–2403. IEEE (2013)
Zhong, Y., Jain, A.K., Dubuisson-Jolly, M.-P.: Object tracking using deformable templates. IEEE Trans. Pattern Anal. Mach. Intell. 22(5), 544–549 (2000)
Berclaz, J., Fleuret, F., Turetken, E., Fua, P.: Multiple object tracking using K-shortest paths optimization. IEEE Trans. Pattern Anal. Mach. Intell. 1–16 (2011)
Gevers, T.: Robust segmentation and tracking of colored objects in video. IEEE Trans. Circ. Syst. Video Technol. 776–780 (2004)
Koo, S., Lee, D., Kwon, D.-S.: Multiple object tracking using an RGB-D camera by hierarchical spatiotemporal data association. In: International Conference on Intelligent Robots and Systems (IROS), pp. 1113–1118. IEEE (2013)
Acknowledgement
We would like to acknowledge the contribution of the School of Computer Sciences, USM and the RU Grant (1001/PKOMP/817070) from USM. We would also like to thank the MFUC (Malaysia France University Centre) for their support in the cotutelle program between Universiti Sains Malaysia and Université de La Rochelle.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this paper
Cite this paper
Lee, W.P., Osman, M.A., Talib, A.Z., Yahya, K., Burie, JC., Ogier, JM. (2015). Enhanced Object Tracking in Real-Time Environment Using Dual Camera. In: Badioze Zaman, H., et al. Advances in Visual Informatics. IVIC 2015. Lecture Notes in Computer Science(), vol 9429. Springer, Cham. https://doi.org/10.1007/978-3-319-25939-0_27
Download citation
DOI: https://doi.org/10.1007/978-3-319-25939-0_27
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-25938-3
Online ISBN: 978-3-319-25939-0
eBook Packages: Computer ScienceComputer Science (R0)