Lightweight generic random ferns for multi-target augmented reality on mobile devices

Abstract

Proposed use lightweight generic random ferns (LGRF), a fast key-point classifier designed for multi-target augmented reality (AR) on mobile devices. LGRF uses binary features of image patches for both object recognition and keypoint matching of multiple objects, and stores probabilities in a single bit representation to reduce memory requirements. As a result, LGRF can perform simultaneous object recognition and keypoint matching in real time with low memory consumption, making it suitable for multi-target AR on mobile devices.