• The KIPS Transactions:PartB
• /
• v.15B no.3
• /
• pp.197-204
• /
• 2008

It is well known that the tracking a certain person is a vary needed technic in the humanoid robot. In robot technic, we should consider three aspects that is cloth color matching, face recognition and motion analysis. Because a robot technic use some sensors, it is many different with the robot technic to track a certain person through the CCTV images. A system speed should be fast in CCTV images, hence we must have small calculation numbers. We need the statistical variable for color matching and we adapt the eigen-face for face recognition to speed up the system. In this situation, motion analysis have to added for the propose of the efficient detecting system. But, in many motion analysis systems, the speed and the recognition rate is low because the system operates on the all image area. In this paper, we use the moving energy only on the face area which is searched when the face recognition is processed, since the moving energy has low calculation numbers. When the proposed algorithm has been compared with Girondel, V. et al's method for experiment, we obtained same recognition rate as Girondel, V., the speed of the proposed algorithm was the more faster. When the LDA has been used, the speed was same and the recognition rate was better than Girondel, V.'s method, consequently the proposed algorithm is more efficient for tracking a certain person.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.9 no.5
• /
• pp.205-211
• /
• 2009

The Weightless Neural Network(WNN) has the advantage of the processing speed, less computability than weighted neural network which readjusts the weight. Especially, The behavior information such as sequential gesture has many serial correlation. So, It is required the high computability and processing time to recognize. To solve these problem, Many algorithms used that added preprocessing and hardware interface device to reduce the computability and speed. In this paper, we proposed the Ram based Sequential Cumulative Neural Network(SCNN) model which is sign language recognition system without preprocessing and hardware interface. We experimented with using compound words in continuous korean sign language which was input binary image with edge detection from camera. The recognition system of sign language without preprocessing got 93% recognition rate.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.13 no.10
• /
• pp.4801-4806
• /
• 2012

There are still problems have to solve for safety of driving comparing to the upgraded convenience of advanced vehicle. Most traffic accident is by uncareful driving cause of interface operations which are directive reasons of it in controlling the complicate multimedia device. According to interesting in smart automobile, various approaches for safe driving have been studied. The current multimedia interface embedded in vehicle is lacking the safety due to loss the sense and operation capacity by instantaneous view movement. In this paper, we propose a safe dialing system for safe driving to control dial and search dictionary by hand-gesture. The proposed system improved the user convenience and safety in automobile operation using intuitive gesture and TTS(Text to Speech).

• Journal of The Korean Association of Information Education
• /
• v.19 no.1
• /
• pp.69-76
• /
• 2015

In current information society, there is a barrier called digital divide. Due to this barrier, the disabled have difficulties to communicate with the world. Recently, with advanced smart techniques, smart devices become necessity for the disabled. Currently improvements of smart application accessibility become a great concern for the disabled. The purpose of this paper is to present some guidelines for enhancing smart application accessibility for the disabled. The enhancement guidelines are developed based on the existing mobile accessibility guidelines and modified for better adaptability for the disabled. Our principles are as follows: minimizing blue light emission from smart devices, automatic focus on input window, action trace, font color change, emergency notification by motion, gesture recognition, control location, scrolling avoidance, auditory service for visual warning, and icon literation.

• Journal of Korea Multimedia Society
• /
• v.15 no.6
• /
• pp.827-836
• /
• 2012

After successful advent of Microsoft's Kinect, many interactive contents that control user's 3D avatar motions in realtime have been created. However, due to the Kinect's intrinsic IR projection problem, users are restricted to face the sensor directly forward and to perform all motions in a standing-still position. These constraints are main reasons that make it almost impossible for the 3D character to navigate the virtual environment, which is one of the most required functionalities in games. This paper proposes a new method that makes 3D character navigate the virtual environment with highly realistic motions. First, in order to find out the user's intention of navigating the virtual environment, the method recognizes walking-in-place motion. Second, the algorithm applies the motion splicing technique which segments the upper and the lower motions of character automatically and then switches the lower motion with pre-processed motion capture data naturally. Since the proposed algorithm can synthesize realistic lower-body walking motion while using motion capture data as well as capturing upper body motion on-line puppetry manner, it allows the 3D character to navigate the virtual environment realistically.

• Proceedings of the Korea Contents Association Conference
• /
• 2009.05a
• /
• pp.175-178
• /
• 2009

In this paper, we describe about interactive electronic book utilizing tabletop display interface and digi-pet. Because of this system can define a lot of gestures using touch point of finger, help that user experiences electronic book effectively more than existent input device. Also, support 1 users in 1 input device in existent mode, but this system can expect various effect because support Multi-user. The digi-pet(digital pet) is physical tools that convey emotion between tabletop display platform and user. And this shows various results acting as assistance because becomes master of story of imagination and participate directly on talk and makes change of story. In this paper, we described about oriented electronic book system the future that combines tabletop display and Digi-pet. This system is expected that the usefulness is increased by leaps and bounds along with technology development forward.

• Journal of the Institute of Electronics Engineers of Korea TC
• /
• v.43 no.1 s.343
• /
• pp.127-132
• /
• 2006

This paper presents a dual-mode amplifier which operates as amplifier or frequency multiplier according to the input frequency. It satisfies the 802.11a/b/g frequency band of wireless LAN standard. A conventional dual-band wireless LAN transmitter consists of the separating power amplifiers operating at each frequency band, but the proposed dual-mode amplifier operates as an amplifier for the 802.11b/g signal and as a frequency multiplier for the 802.11a signal according to each LAN bias condition. The amplifier mode shows the gain of 13dB, the PldB of 17dBm and second harmonic suppression of below -37dBc. And the frequency-doubler mode shows the gain of 3.3dB, the output power of 7.3dBm and third harmonic suppression of below -50dBr.

• The Journal of Korea Robotics Society
• /
• v.8 no.1
• /
• pp.1-7
• /
• 2013

Body gesture Recognition has been one of the interested research field for Human-Robot Interaction(HRI). Most of the conventional body gesture recognition algorithms used Hidden Markov Model(HMM) for modeling gestures which have spatio-temporal variabilities. However, HMM-based algorithms have difficulties excluding meaningless gestures. Besides, it is necessary for conventional body gesture recognition algorithms to perform gesture segmentation first, then sends the extracted gesture to the HMM for gesture recognition. This separated system causes time delay between two continuing gestures to be recognized, and it makes the system inappropriate for continuous gesture recognition. To overcome these two limitations, this paper suggests primitive body model encoding, which performs spatio/temporal quantization of motions from human body model and encodes them into predefined primitive codes for each link of a body model, and Selective/Asynchronous Input-Parallel State machine(SAI-PSM) for multiple-simultaneous gesture recognition. The experimental results showed that the proposed gesture recognition system using primitive body model encoding and SAI-PSM can exclude meaningless gestures well from the continuous body model data, while performing multiple-simultaneous gesture recognition without losing recognition rates compared to the previous HMM-based work.

• Science of Emotion and Sensibility
• /
• v.14 no.4
• /
• pp.627-636
• /
• 2011

The purpose of this study is to develop the multi-modal interaction system. This system provides realistic and an immersive experience through multi-modal interaction. The system recognizes user behavior, intention, and attention, which overcomes the limitations of uni-modal interaction. The multi-modal interaction system is based upon gesture interaction methods, intuitive gesture interaction and attention evaluation technology. The gesture interaction methods were based on the sensors that were selected to analyze the accuracy of the 3-D gesture recognition technology using meta-analysis. The elements of intuitive gesture interaction were reflected through the results of experiments. The attention evaluation technology was developed by the physiological signal analysis. This system is divided into 3 modules; a motion cognitive system, an eye gaze detecting system, and a bio-reaction sensing system. The first module is the motion cognitive system which uses the accelerator sensor and flexible sensors to recognize hand and finger movements of the user. The second module is an eye gaze detecting system that detects pupil movements and reactions. The final module consists of a bio-reaction sensing system or attention evaluating system which tracks cardiovascular and skin temperature reactions. This study will be used for the development of realistic digital entertainment technology.

• Journal of KIISE:Software and Applications
• /
• v.36 no.10
• /
• pp.836-850
• /
• 2009

Human posture recognition has attracted tremendous attention in ubiquitous environment, performing arts and robot control so that, recently, many researchers in pattern recognition and computer vision are working to make efficient posture recognition system. However the most of existing studies is very sensitive to human variations such as the rotation or the translation of body. This is why the feature, which is extracted from the feature extraction part as the first step of general posture recognition system, is influenced by these variations. To alleviate these human variations and improve the posture recognition result, this paper presents 3D Star Skeleton and Principle Component Analysis (PCA) based feature extraction methods in the multi-view environment. The proposed system use the 8 projection maps, a kind of depth map, as an input data. And the projection maps are extracted from the visual hull generation process. Though these data, the system constructs 3D Star Skeleton and extracts the rotation invariant feature using PCA. In experimental result, we extract the feature from the 3D Star Skeleton and recognize the human posture using the feature. Finally we prove that the proposed method is robust to human variations.