Pictorial Portrait Indexing Using View-Based Eigen-Eyes
VISUAL '99 Proceedings of the Third International Conference on Visual Information and Information Systems
The Memory Glasses: Subliminal vs. Overt Memory Support with Imperfect Information
ISWC '03 Proceedings of the 7th IEEE International Symposium on Wearable Computers
Compressive Sensing for Background Subtraction
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part II
Evolution of 3G Networks: The Concept, Architecture and Realization of Mobile Networks Beyond UMTS
Evolution of 3G Networks: The Concept, Architecture and Realization of Mobile Networks Beyond UMTS
IEEE Transactions on Information Theory
Efficient background subtraction for real-time tracking in embedded camera networks
Proceedings of the 10th ACM Conference on Embedded Network Sensor Systems
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More than 30% of the world population have vision defects, for some of which causes are still unclear. Visual health monitoring for detection, prevention, and treatment is possible but still very limited due to limited access to expensive specialized equipment and domain experts. Therefore, it is difficult to provide long-term visual health monitoring for a large population. In this paper, we present the design and evaluation of Cyber Glasses, low-cost computational glasses as a step toward long-term large-scale human visual health monitoring. At the core of Cyber Glasses are three key novel contributions: an integration of low-cost commercial off the shelf (COTS) components, an adaptive data collection mechanism taking into account tradeoffs between sensing accuracy, latency, memory, and energy, and a suit of energy efficient algorithms to reduce sensor data size and to extract meaningful human vision information to high-level applications. We conduct a number of experiments to verify the feasibility of Cyber Glasses to enable long-term large-scale human visual health monitoring.