Feature selection for low bit rate mobile augmented reality applications

Usability testing method in augmented reality application

“…As result an effective and simple multicamera collaborative tracking approach which proposed that can overcome occlusion problem in augmented reality applications and reduce uncomfortable experience for the user caused by the temporary unavailability of tracking units [31]. Yi Cao et al [32] research measure Number of image matches between image in dataset and image in data references, image dataset is given little distortion to test whether the tried algorithm still delivers results with high accuracy. Yi Cao et all extracted each image in dataset: extract the featured, and select specific number features as proposed features and perform kdimensional (KD) to produce training structure to obtains the references feature search spaces, the augmented reality application perform the nearest neighbour search using KNN (k=1) and conducted verification using geometry verification (RANSAC) to ensure positive matching.…”