Emerging mobile applications are increasingly focused on technology interacting with and augmenting the real-world environment the user occupies. Augmented reality is a technology that places virtual objects on a user?s view of the real world with a wide range of applications such as navigation, gaming, and education. Augmented reality as a technology is inherently extremely computation-heavy, leading to latency, accuracy, and energy-consumption issues on resource-constrained smartphones. Image-recognitio- based augmented reality compounds this issue by requiring the computation of the entire image-recognition pipeline. In addition, mobile hardware is not designed with augmented reality and heavy image-based computations in mind. Mobile caching, multicores, GPUs and other mobile architectures are not being utilized to their full potential to help resolve the issues plaguing mobile augmented reality. This project explores methods to utilize the unique mobile architecture of off-the-shelf smartphones in new ways to realize augmented reality on a wide variety of mobile devices. Specifically, augmented reality has become an important tool for educators at all levels from K-12 all the way through collegiate and post-graduation education. This project will allow for this new educational technology to be more widely utilized in the world.
The objective of this project is to enable smartphones to support augmented reality via efficiently and seamlessly computing image-recognition and world-tracking tasks simultaneously, with three research components. (1) Investigate the foundational issues of smartphone-based augmented-reality through approximate-tracking to provide high-quality object tracking at reduced computational and energy loads. (2) Research software-defined caching techniques to utilize the unique nature of mobile augmented reality to provide caching specially designed for highly collaborative device-to-device augmented reality. (3) Explore hardware-based techniques relating to GPGPU computation and cache management to facilitate fast and efficient image-recognition and augmented-reality tasks.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
