Recently, head-mounted display (HMD) has been actively developed for next-generation smart device. The advanced HMD requires a low-power operation of several algorithms such as object recognition, 3D graphics rendering, and convenient user interface and user experience (UIUX), which are difficult to achieve real-time performance with low-power consumption even on today’s state-of-the-art processors. Despite of the complexity of the algorithms, HMD is battery-driven device that should run several hours to days. These requirements of the mobile HMD system motivate our research to design real-time object recognition and UI/UX with low-power consumption. To achieve real-time and low-power HMD system, four different researches are carried out; Algorithm, Architecture, VLSI implementation, Humanistic intelligence.
   For algorithm research, we develop new object recognition algorithm and deep learning to retain higher accuracy as well as lower computation cost than conventional works. It exploits visual attention process of human brain so as to increase recognition accuracy and speed. Based on the new algorithm, a heterogeneous many-core processor is designed with the visual attention engine adopting massively parallel architecture for high throughput. After that, power and task management techniques, such as DVFS, power gating and dynamic resource management, are applied to the VLSI implementation of the processor. To realize humanistic intelligence on our SoC, we employ the way of human thinks, learns and understands which overcome limitations of A.I. into our research. These studies obtained spotlights as a competing device to Google Glass.