A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2018; you can also visit the original URL.
The file type is
Proceedings of the 5th International Symposium on Knowledge Acquisition and Modeling
This paper investigates and proposes an improved Meanshift algorithm combined with Kalman Filter aiming at the shortcomings of the Meanshift algorithm theory as well as obvious limitations of a target tracking for the independent visual robotic fish being affected by the fluctuation of the water wave. First, this new algorithm makes use of Kalman filter to obtain the initial position of the Meanshift algorithm. Then, adjust the bandwidth of the kernel function adaptively in the Meanshiftdoi:10.2991/kam-15.2015.46 fatcat:e257kucnxnh37fbelip6nqk56u