Enhanced Object Tracking in Real-Time Environment Using Dual Camera
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.
KeywordsObject tracking Single camera Dual camera Fish tracking
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.
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