An improved algorithm of median flow for visual object tracking and its implementation on ARM platform

An improved algorithm of median flow used for visual object tracking is described. The improvement consists in adaptive selection of aperture window size and number of pyramid levels at optical flow estimation. It can increase the tracking efficiency as compared to the basic algorithm, especially when dealing with small and low-contrast objects. The proposed version of the algorithm has been implemented using OpenCV library and tested on OMAP 35x EVM and BeagleBoard-xM based on Texas Instruments OMAP3530 and DM3730 processors, respectively. Analysis of improved median flow was performed over actual video sequences. The results obtained show versatility and computational robustness of the algorithm, which makes it promising for embedded application based on ARM processors.

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