An extended Real-Time Compressive Tracking Method using weighted multi-frame Cosine Similarity Metric

This paper presents an extended algorithm for Real-time Compressive Tracking using Cosine Similarity Metric for object tracking. The method utilises a weighted multi-frame cosine similarity metric with the ground truth bounding box and a recently computed target bounding box. In comparison to the original algorithm it is capable of handling fast motion with a greater degree of accuracy. The proposed algorithm has been benchmarked on a desktop computer and subsequently implemented on a Texas Instruments ARM based DM3730 Beagleboard-xM. The proposed algorithm demonstrates a significant performance increase in fast motion video sequences. In addition, the low computational complexity of the algorithm makes it well suited for embedded applications.