• Journal of the Korea Convergence Society
• /
• v.5 no.4
• /
• pp.1-7
• /
• 2014

Gesture recognition provides the ease and immediacy to users in the processing technique for recognizing the gesture. Because of these benefits, gesture recognition technology has been applied and fused in many areas, such as the military, health care, education. In particular, the gesture recognition in game field since it can provide users to play games similar to the actual gesture, it being fused with many areas such as medical, military, and education. This paper is to discuss the future convergence direction of motion recognition games based on this background. In this paper, it looks at technology status and the game of gesture recognition, describe the problem and improvement of gesture recognition game. This paper can help improving the competitiveness of domestic convergence on gesture recognition game.

• Journal of KIISE:Software and Applications
• /
• v.31 no.12
• /
• pp.1581-1590
• /
• 2004

We present a robust off-line method recognizing handwritten digits by only using stroke direction codes as a feature of handwritten digits. This method makes general 8-direction codes for an input digit and then has the multi-layered neural networks learn them and recognize each digit. The 8-direction codes are made of the thinned results of each digit through SOG*(Improved Self-Organizing Graph). And the usage of these codes simplifies the complex steps processing at least two features of the existing methods. The experimental result shows that the recognition rates of this method are constantly better than 98.85% for any images in all digit databases.

• IEMEK Journal of Embedded Systems and Applications
• /
• v.7 no.1
• /
• pp.33-39
• /
• 2012

In this paper, we propose robot control interface using gaze recognition which is not limited by head motion. Most of the existing gaze recognition methods are working well only if the head is fixed. Furthermore the methods require a correction process per each person. The interface in this paper uses a camera with built-in infrared filter and 2 LED light sources to see what direction the pupils turn to and can send command codes to control the system, thus it doesn't need any correction process per each person. The experimental results showed that the proposed interface can control the system exactly by recognizing user's gaze direction.

• Proceedings of the Korean Information Science Society Conference
• /
• 2007.10c
• /
• pp.263-266
• /
• 2007

We introduce a vision-based hand gesture recognition fer understanding musical time and patterns without extra special devices. We suggest a simple and reliable vision-based hand gesture recognition having two features First, the motion-direction code is proposed, which is a quantized code for motion directions. Second, the conducting feature point (CFP) where the point of sudden motion changes is also proposed. The proposed hand gesture recognition system extracts the human hand region by segmenting the depth information generated by stereo matching of image sequences. And then, it follows the motion of the center of the gravity(COG) of the extracted hand region and generates the gesture features such as CFP and the direction-code finally, we obtain the current timing pattern of beat and tempo of the playing music. The experimental results on the test data set show that the musical time pattern and tempo recognition rate is over 86.42% for the motion histogram matching, and 79.75% fer the CFP tracking only.

• ETRI Journal
• /
• v.46 no.2
• /
• pp.250-262
• /
• 2024

Air-writing recognition is relevant in areas such as natural human-computer interaction, augmented reality, and virtual reality. A trajectory is the most natural way to represent air writing. We analyze the recognition accuracy of words written in air considering five features, namely, writing direction, curvature, trajectory, orthocenter, and ellipsoid, as well as different parameters of a hidden Markov model classifier. Experiments were performed on two representative datasets, whose sample trajectories were collected using a Leap Motion Controller from a fingertip performing air writing. Dataset D₁ contains 840 English words from 21 classes, and dataset D₂ contains 1600 English words from 40 classes. A genetic algorithm was combined with a hidden Markov model classifier to obtain the best subset of features. Combination ftrajectory, orthocenter, writing direction, curvatureg provided the best feature set, achieving recognition accuracies on datasets D₁ and D₂ of 98.81% and 83.58%, respectively.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.16 no.6
• /
• pp.1187-1192
• /
• 2012

This paper describes a method to detect QR-code finders by four-direction scanning. The finder recognition is the first step in the QR-code recognition. If the finder is missing, QR-code recognition fails. The existing QR-code recognition method has a problem that the recognition performance decreases for perspectively distored images. To overcome the problem, we introduce four-direction scanning and a candidate set image to accurately detect QR-code finders. Using morphological operations detect the QR-code finder in the candidate set image robustly. To show the effectiveness of our method, we compared our method with the well-known existing method. The experimental result indicates that the proposed method is superior to the existing method in terms of the finder recognition performance.

• 제어로봇시스템학회:학술대회논문집
• /
• 2003.10a
• /
• pp.633-638
• /
• 2003

In this paper, we propose a humanoid active audition system which detects the direction of sound and performs speech recognition using just three microphones. Compared with previous researches, this system which has simpler algorithm, fewer microphones and better amplifier shows better performance. In order to verify our system's performance, we install the proposed active audition system to the home service robot, called Hombot II, which has been developed at the KIST (Korea Institute of Science and Technology), thus we confirm excellent performance by experimental results

• The Transactions of the Korean Institute of Electrical Engineers D
• /
• v.52 no.9
• /
• pp.526-532
• /
• 2003

This paper describes a recognition method of a road direction for an autonomous vehicle based on magnetic sensors. Using the sensors mounted on a vehicle and the magnetic markers embedded along the center of road, the autonomous vehicle can recognize a road direction and control a steering angle. Using the front lateral deviation of a vehicle and the rear one, the road direction is calculated. The analysis of magnetic field, the acquisition technique of training data, the training method of neural network and the computer simulation are presented. According to the computer simulation, the proposed method is simulated, and its performance is verified. Also, the experimental test is confirmed its reliability.

• Journal of the Korean Data and Information Science Society
• /
• v.14 no.3
• /
• pp.525-533
• /
• 2003

In this paper we introduce some existing preprocessing algorithm for character recognition and consider feature extraction method for the recognition of low resolution document. Image recognition of low resolution document including fax images can be frequently misclassified due to the blurring effect, slope effect, noise and so on. In order to overcome these difficulties in the character recognition we considered a mesh feature extraction and contour direction code feature. System for automatic character recognition were suggested.

• Journal of Digital Convergence
• /
• v.13 no.9
• /
• pp.259-267
• /
• 2015

In this paper, we proposed the straight line determination method and the algorithm for 8 directions determination of straight line using the coordinate information and the property of trigonometric function. We conduct an experiment that is 8 hand gestures are carried out 100 times each, a total of 800 times. And the accuracy for the 8 derection determination algorithm is showed the diagonal direction to the left upper side shows the highest accuracy as 92%, and the direction to the left side, the diagonal direction to the right upper side and the diagonal direction to the right bottom side show the lowest accuracy as 82%. This method with coordinate information through image processing than the existing recognizer and the recognition through learning process is possible using a hand gesture recognition gesture.