• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.5
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• pp.622-629
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• 2019

VR(Virtual Reality), which provides realistic services in virtual reality, provides a similar experience using a Head Mounted Display(HMD) device. When the HMD device is worn, it can not recognize the surrounding environment and it is easy to analyze the input pattern of the user with the Shoulder Surfing Attack(SSA) when entering the Personal Identification Number(PIN). In this paper, we propose a method to safeguard the user's password even if the hacker analyzes the input pattern while maintaining the user's convenience. For the first time, we implemented a new type of virtual keypad that deviates from the existing rectangle shape according to the VR characteristics and implemented the lock object for intuitive interaction with the user. In addition, a smart glove using the same sensor as the existing input devices of the VR and a PIN input method suitable for the rotary type are implemented and the safety of the SSA is verified through experiments.

• Journal of KIISE:Software and Applications
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• v.35 no.12
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• pp.780-788
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• 2008

Modeling hand poses and tracking its movement are one of the challenging problems in computer vision. There are two typical approaches for the reconstruction of hand poses in 3D, depending on the number of cameras from which images are captured. One is to capture images from multiple cameras or a stereo camera. The other is to capture images from a single camera. The former approach is relatively limited, because of the environmental constraints for setting up multiple cameras. In this paper we propose a method of reconstructing 3D hand poses from a 2D input image sequence captured from a single camera by means of Belief Propagation in a graphical model and recognizing a finger clicking motion using a hidden Markov model. We define a graphical model with hidden nodes representing joints of a hand, and observable nodes with the features extracted from a 2D input image sequence. To track hand poses in 3D, we use a Belief Propagation algorithm, which provides a robust and unified framework for inference in a graphical model. From the estimated 3D hand pose we extract the information for each finger's motion, which is then fed into a hidden Markov model. To recognize natural finger actions, we consider the movements of all the fingers to recognize a single finger's action. We applied the proposed method to a virtual keypad system and the result showed a high recognition rate of 94.66% with 300 test data.

• Archives of design research
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• v.17 no.3
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• pp.441-448
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• 2004

Mobile devices such as mobile phones or PDAs are considered as main interlace tools in ubiquitous computing environment. For searching information in mobile device, it should be possible for user to input some text as well as to control cursor for navigation. So, we should find efficient interlace method for text input in limited dimension of mobile devices. This study intends to suggest a new approach to mobile interaction using camera based virtual keyboard for text input in mobile devices. We developed a camera based virtual keyboard prototype using a PC camera and a small size LCD display. User can move the prototype in the air to control the cursor over keyboard layout in screen and input text by pressing a button. The new interaction method in this study is evaluated as competitive compared to mobile phone keypad in left input efficiency. And the new method can be operated by one hand and make it possible to design smaller device by eliminating keyboard part. The new interaction method can be applied to text input method for mobile devices requiring especially small dimension. And this method can be modified to selection and navigation method for wireless internet contents on small screen devices.