• Journal of Digital Convergence
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• v.12 no.2
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• pp.373-378
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• 2014

To investigate the wear status of contact lenses by analyzing care of contact lenses container and actual condition of people wearing contact lenses and in Gyeonggido. The results were based on a questionnaire survey of 200 people who are the students of the middle school, the high school and the college among the clients of opticians to purchase contact lenses for six months from January 2013 to July 2013. According to the poll, the highest number of those polled, 139 (55.16%) people, said they were wearing cosmetic color contact lenses. Female respondents and male respondents were in the proportion of 177 (88.5%) to 23 (11.5%), respectively. 37 people (18.5%) who responded said "yes" to the question of them sharing contact lenses and glasses. 103 people (51.5%) answered "no" to the question of regularly replacing their lens containers. 148 people (74%) answered "yes" to the question of having glasses in order to investigate contact lens wearers user rate of glasses. The highest number of respondents, 127 people (63.5%), said "middle school" was the first time that they wore contacts. Meanwhile, 65 people (43.92%) said they initiated wearing glasses at 4th-6th grades. It is considered that it is necessary using proper contact lenses suitable for the clients' eye health in order of vision correction, rather than for cosmetic purposes. The role of the optician is considered to be very important for the proper management of the appropriate contact lens hygiene and regular optical check-ups of the contact lens wearers.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.2
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• pp.143-149
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• 2019

Floating holograms are technologies that provide rich 3D stereoscopic images in a wide space such as advertisement, concert. In addition, It is possible to reduce the 3D glasses inconvenience, eye strain, and space distortion, and to enjoy 3D images with excellent realism and existence. Therefore, this paper implements a user gesture recognition system for manipulating a floating hologram characters that can be used in a small space devices. The proposed method detects face region using haar feature-based cascade classifier, and recognizes the user gestures using a user gesture-occurred position information that is acquired from the gesture difference image in real time. And Each classified gesture information is mapped to the character motion in floating hologram for manipulating a character action. In order to evaluate the performance of the proposed user gesture recognition system for manipulating a floating hologram character, we make the floating hologram display devise, and measures the recognition rate of each gesture repeatedly that includes body shaking, walking, hand shaking, and jumping. As a results, the average recognition rate was 88%.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.8 no.6
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• pp.491-496
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• 2015

Cloud computing has emerged with promise to decrease the cost of server additional cost and expanding the data storage and ease for computer resource sharing and apply the new technologies. However, Cloud computing also raises many new security concerns due to the new structure of the cloud service models. Therefore, the secure user authentication is required when the user is using cloud computing. This paper, we propose the enhanced AdaBoost algorithm for access cloud security zone. The AdaBoost algorithm despite the disadvantage of not detect a face inclined at least 20, is widely used because of speed and responsibility. In the experimental results confirm that a face inclined at least 20 degrees tilted face was recognized. Using the FEI Face Database that can be used in research to obtain a result of 98% success rate of the algorithm perform. The 2% failed rate is due to eye detection error which is the people wearing glasses in the picture.

• Journal of Broadcast Engineering
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• v.23 no.2
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• pp.246-252
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• 2018

Hand gestures are attracting attention as a NUI (Natural User Interface) of wearable devices such as smart glasses. Recently, to support efficient media consumption in IoT (Internet of Things) and wearable environments, the standardization of IoMT (Internet of Media Things) is in the progress in MPEG. In IoMT, it is assumed that hand gesture detection and recognition are performed on a separate device, and thus provides an interoperable interface between these modules. Meanwhile, deep learning based hand gesture recognition techniques have been recently actively studied to improve the recognition performance. In this paper, we propose a method of hand gesture recognition based on CNN (Convolutional Neural Network) for various applications such as media consumption in wearable devices which is one of the use cases of IoMT. The proposed method detects hand contour from stereo images acquisitioned by smart glasses using depth information and color information, constructs data sets to learn CNN, and then recognizes gestures from input hand contour images. Experimental results show that the proposed method achieves the average 95% hand gesture recognition rate.