Holographic optical elements: State-of-the-art review: Part 2

This is the second part of a two part review on the state-of-the-art in holographic optical elements (HOEs). The aspects of fabrication, evaluation, and applications of HOEs, are discussed in this part. It details the direction of future efforts towards finding work-horse type recording media, developing new methods for the evaluation of HOE, and identifying the areas of application where HOEs are to be considered as indispensable components/tools. Finally a summary of all the suggestions for future work made in the two parts is displayed in Table 2 of this part of the review.

VISUAL OBJECT TRACKING VIA RANDOM FERNS BASED CLASSIFICATION

Designing a robust algorithm for visual object tracking has been a challenging task since many years. There are trackers in the literature that are reasonably accurate for many tracking scenarios but most of them are computationally expensive. This narrows down their applicability as many tracking applications demand real time response. In this paper, we present a tracker based on random ferns. Tracking is posed as a classification problem and classification is done using ferns. We used ferns as they rely on binary features and are extremely fast at both training and classification as compared to other classification algorithms. Our experiments show that the proposed tracker performs well on some of the most challenging tracking datasets and executes much faster than one of the state-of-the-art trackers, without much difference in tracking accuracy.