Visual tracking with randomly projected ferns

• We introduce random projection into random ferns and propose random projection ferns.
• Our approach needs very few memory and computing resources.
• Our approach is simple to implement and runs very fast.

In this paper, a novel visual tracking method based on random ferns and random projection has been proposed. Instead of a binary comparison in the standard random ferns method, a subtraction is used in the proposed method. Different subtraction results are projected into a single real value by the random projection. The real value from the subtraction is more informative than a binary comparison, thus less subtractions are needed. More importantly, the proposed method has a constant memory resource requirement independent from the number of subtractions in each fern, whereas in a standard random ferns method, the requirement is an exponential relationship with the number of binary comparisons. Besides low memory requirement, our approach is also computational efficient. Experimental results demonstrate that the proposed method performs better than the standard random ferns method and some other methods, especially in memory and computing resources requirements, which are of vital importance in some embedded systems.