• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.3
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• pp.251-256
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• 2019

In this paper we proposed system and algorithm to recognize hand gestures based on the millimeter wave that is in 65GHz bandwidth. The proposed system is composed of millimeter wave radar board, analog to data conversion and data capture board and notebook to perform gesture recognition algorithms. As feature vectors in proposed algorithm. we used global and local zernike moment descriptor which are robust to distort by rotation of scaling of 2D data. As Experimental result, performance of the proposed algorithm is evaluated and compared with those of algorithms using single global or local zernike descriptor as feature vectors. In analysis of confusion matrix of algorithms, the proposed algorithm shows the better performance in comparison of precision, accuracy and sensitivity, subsequently total performance index of our method is 95.6% comparing with another two mehods in 88.4% and 84%.

• Journal of the Ergonomics Society of Korea
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• v.32 no.2
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• pp.179-187
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• 2013

Objective: The purpose of this study is to extract GOMS manual operator, except for an experiment with participants. Background: The GOMS model has advantage of rapid modeling which is suitable for the environment of technology development which has a short life cycle products with a fast pace. The GOMS model was originally designed for desktop environment so that it is not adequate for implementing into the latest HCI environment such as small touch screen device. Therefore, this research proposed GOMS manual operator extraction methodology which is excluded experimental method. And flick Gesture was selected to explain application of proposed methodology to extract new operator. Method: Divide into start to final step of hand gesture needed to extract as an operator through gesture task analysis. Then apply the original GOMS operator to each similar step of gesture and modify the operator for implementation stage based on existing Fitts' law research. Steps that are required to move are modified based on the Fitts' law developed in touch screen device. Finally, new operator can be derived from using these stages and a validation experiment, performed to verify the validity of new operator and methodology by comparing human performance. Results: The average movement times of the participants' performance and the operator which is extracted in case study are not different significantly. Also the average of movement times of each type of view study is not different significantly. Conclusion: In conclusion, the result of the proposed methodology for extracting new operator is similar to the result of the experiment with their participants. Furthermore the GOMS model included the operator by the proposed methodology in this research could be applied successfully to predict the user's performance. Application: Using this methodology could be applied to develop new finger gesture in the touch screen. Also this proposed methodology could be applied to evaluate the usability of certain system rapidly including the new finger gesture performance.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1995.10b
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• pp.85-91
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• 1995

This paper presents a system which recognizes the Korean Sign Language(KSL) and translates into normal Korean speech. A sign language is a method of communication for the deaf-mute who uses gestures, especially both hands and fingers. Since the human hands and fingers are not the same in physical dimension, the same form of a gesture produced by two signers with their hands may not produce the same numerical values when obtained through electronic sensors. In this paper, we propose a dynamic gesture recognition method based on feature analysis for efficient classification of hand motions, and on a fuzzy min-max neural network for on-line pattern recognition.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.10
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• pp.171-180
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• 2013

Generally, when we apply zernike moments value for matching, we can use those moments value obtained from projecting image information under circumscribed circle to zernike basis function. However, the problem is that the power of discrimination can be reduced because hand images include lots of overlapped information due to its special characteristic. On the other hand, when distinguishing hand poses, information in specific area of image information except for overlapped information can increase the power of discrimination. In this paper, in order to solve problems like those, we design R3 ring mask by combining image obtained from R2 ring mask, which can weight information of the power of discrimination and image obtained from R1 ring mask, which eliminate the overlapped information. The moments which are obtained by R3 ring mask decrease operational time by reducing dimension through principle component analysis. In order to confirm the superiority of the suggested method, we conducted some experiments by comparing our method to other method using seven different hand poses.

• The KIPS Transactions:PartB
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• v.13B no.5 s.108
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• pp.561-568
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• 2006

WPS(Wearable Personal Station) for next generation PC can define as a core terminal of 'Ubiquitous Computing' that include information processing and network function and overcome spatial limitation in acquisition of new information. As a way to acquire significant dynamic gesture data of user from haptic devices, traditional gesture recognizer based on desktop-PC using wire communication module has several restrictions such as conditionality on space, complexity between transmission mediums(cable elements), limitation of motion and incommodiousness on use. Accordingly, in this paper, in order to overcome these problems, we implement hand gesture recognition system using fuzzy algorithm and neural network for Post PC(the embedded-ubiquitous environment using blue-tooth module and WPS). Also, we propose most efficient and reasonable hand gesture recognition interface for Post PC through evaluation and analysis of performance about each gesture recognition system. The proposed gesture recognition system consists of three modules: 1) gesture input module that processes motion of dynamic hand to input data 2) Relational Database Management System(hereafter, RDBMS) module to segment significant gestures from input data and 3) 2 each different recognition modulo: fuzzy max-min and neural network recognition module to recognize significant gesture of continuous / dynamic gestures. Experimental result shows the average recognition rate of 98.8% in fuzzy min-nin module and 96.7% in neural network recognition module about significantly dynamic gestures.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.3
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• pp.199-204
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• 2013

An implementation method of real-time numeral recognizer based on gesture is presented in this paper for various information devices. The proposed algorithm steadily captures the motion of a hand on 3D open space with the Kinect sensor. The captured hand motion is simplified with PCA, in order to preserve the trace consistency and to minimize the trace variations due to noises and size changes. In addition, we also propose a new HMM using both the gradient and the positional features of the simplified hand stroke. As the result, the proposed algorithm has robust characteristics to the variations of the size and speed of hand motion. The recognition rate is increased up to 30%, because of this combined model. Experimental results showed that the proposed algorithm gives a high recognition rate about 98%.

• Journal of Korea Multimedia Society
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• v.8 no.6
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• pp.768-775
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• 2005

For sign languages are main communication means among hearing-impaired people, there are communication difficulties between speaking-oriented people and sign-language-oriented people. Automated sign-language recognition may resolve these communication problems. In sign languages, finger spelling is used to spell names and words that are not listed in the dictionary. There have been research activities for gesture and posture recognition using glove-based devices. However, these devices are often expensive, cumbersome, and inadequate for recognizing elaborate finger spelling. Use of colored patches or gloves also cause uneasiness. In this paper, a vision-based finger spelling recognition system is introduced. In our method, captured hand region images were separated from the background using a skin detection algorithm assuming that there are no skin-colored objects in the background. Then, hand postures were recognized using a two-dimensional grid analysis method. Our recognition system is not sensitive to the size or the rotation of the input posture images. By optimizing the weights of the posture features using a genetic algorithm, our system achieved high accuracy that matches other systems using devices or colored gloves. We applied our posture recognition system for detecting Korean Sign Language, achieving better than $93\%$ accuracy.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.39 no.3
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• pp.62-78
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• 2002

In this paper, we describe a system that can interact with agents in the virtual space incorporated in the system. This system is constructed by an analysis system for analyzing human gesture and an interact system for interacting with agents in the virtual space using analyzed information. An implemented analysis system for analyzing gesture extracts a head and hands region after taking image sequence of an operator's continuous behavior using CCD cameras. In interact system, we construct the virtual space that exist an avatar which incarnating operator himself, an autonomous object (like a Puppy), and non-autonomous objects which are table, door, window and object. Recognized gesture is transmitted to the avatar in the virtual space, then transit to next state based on state transition diagram. State transition diagram is represented in a graph in which each state represented as node and connect with link. In the virtual space, the agent link an avatar can open and close a window and a door, grab or move an object like a ball, order a puppy to do and respond to the Puppy's behavior as does the puppy.

• ETRI Journal
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• v.37 no.4
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• pp.793-803
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• 2015

We propose a novel HMI UI/UX for an in-vehicle infotainment system. Our proposed HMI UI comprises multimodal interfaces that allow a driver to safely and intuitively manipulate an infotainment system while driving. Our analysis of a touchscreen interface-based HMI UI/UX reveals that a driver's use of such an interface while driving can cause the driver to be seriously distracted. Our proposed HMI UI/UX is a novel manipulation mechanism for a vehicle infotainment service. It consists of several interfaces that incorporate a variety of modalities, such as speech recognition, a manipulating device, and hand gesture recognition. In addition, we provide an HMI UI framework designed to be manipulated using a simple method based on four directions and one selection motion. Extensive quantitative and qualitative in-vehicle experiments demonstrate that the proposed HMI UI/UX is an efficient mechanism through which to manipulate an infotainment system while driving.

• The Transactions of the Korea Information Processing Society
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• v.4 no.12
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• pp.3033-3044
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• 1997

This paper presents a system which recognizes dynamic hand gesture for virtual reality (VR). A dynamic hand gesture is a method of communication for human and computer who uses gestures, especially both hands and fingers. Since the human hands and fingers are not the same in physical dimension, the produced by two persons with their hands may not have the same numerical values where obtained through electronic sensors. To recognize meaningful gesture from continuous gestures which have no token of beginning and end, this system segments current motion states using the state automata. In this paper, we apply a fuzzy min-max neural network and feature analysis method using fuzzy logic for on-line pattern recognition.