Performance Analysis of Interaction between Smart Glasses and Smart Objects Using Image-Based Object Identification

Abstract

We propose the use of smart glasses to collaborate with smart objects in the Internet of Things environment. Particularly we are focusing on new interaction methods and the analysis of acceptable reaction times in the process of object recognition using smart glasses. We evaluated the proposed method using user studies and experiments with three different smart glasses: Google Glass, Epson Moverio, and the developed eGlasses platform. We conclude that using the proposed method it is possible to recognize objects and process information allowing object detection below the average acceptance response times specified by almost all participants in the user study. Additionally, we showed that eye-tracking can be used for simple interaction between a user and a graphical user interface presented in the near-to-eye display.

An energy-efficient low-memory image compression system for multimedia IoT products

“…With exciting development of very large-scale integration (VLSI) technology, Internet of things (IoT) products have rapidly evolved into monitoring devices that can capture and stream multimedia data with high-resolution images. Promising multimedia IoT applications include smart glasses [1,2], unmanned aerial vehicles [3], telepresence robots [4], and wireless capsule endoscopies [5] that can capture and transmit still images or video sequences at visually lossless levels. However, processing a high volume of image data and wirelessly transmitting data in a multimedia IoT device that typically has limited battery capacity require high-power consumption.…”