Accelerating mobile augmented reality on a handheld platform

Abstract

Mobile Augmented Reality (MAR) is an emerging visual computing application for the mobile internet device (MID). In one MAR usage model, the user points the handheld device to an object (like a wine bottle or a building) and the MID automatically recognizes and displays information regarding the object. Achieving this in software on the handheld requires significant compute processing for object recognition and matching. In this paper, we identify hotspot functions of the MAR workload on a low-power x86 platform that motivates acceleration. We present the detailed design of two hardware accelerators, one for object recognition (MAR-HA) and the other for match processing (MAR-MA). We also quantify the performance and area efficiency of the hardware accelerators. Our analysis shows that hardware acceleration has the potential to improve the individual hotspot functions by as much as 20x, and overall response time by 7x. As a result, user response time can be reduced significantly.