Real-time Compressive Tracking - A Study and Review
S. Ravi, Salim Guria · 2014
Tracking of objects plays an important role in the security of common man to a country. This includes tracking of objects like human, military vehicle, intruders in the border of every countries. Tracking people and objects plays a vital role now a days as there may be intruders in the border in the name of terrorists. This paper produces a study and review on real time compressive tracking. The image compression also plays an important role as the storage of the images and further the retrieval requires small amount of memory as the available memory space may be scarce. In addition, the processing of the images captured requires faster algorithms. This requires processing of the images as small sized images. This paper analyzed this problem using techniques like compressed tracking and sparse representation. Even though the techniques like, Compressed Tracking, Sparse Representation, Adaptive Filtering, Naive Bayesian Classifier and Mean Shift produces results which is above 90%, Naive Bayes Classifier produces the maximum success rate of 99%.