• The Journal of Korea Robotics Society
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• v.4 no.2
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• pp.139-146
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• 2009

This paper describes how a person extracts a unknown object with pointing gesture while interacting with a robot. Using a stereo vision sensor, our proposed method consists of two stages: the detection of the operators' face, the estimation of the pointing direction, and the extraction of the pointed object. The operator's face is recognized by using the Haar-like features. And then we estimate the 3D pointing direction from the shoulder-to-hand line. Finally, we segment an unknown object from 3D point clouds in estimated region of interest. On the basis of this proposed method, we implemented an object registration system with our mobile robot and obtained reliable experimental results.

• Proceedings of the Acoustical Society of Korea Conference
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• spring
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• pp.165-168
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• 2000

A fast estimation method using wavelet transform for a time delay system is proposed. Main point of this method is to get the wavelet transform of the correlation between the input signal and delayed signal using transformed signals. But wavelet transform using Haar wavelet functions has basis with different phases and can offers a bisection method to estimate a time delay of a signal. Selective computation of the transform of correlation is performed and the computational complexity is reduced. Computational order of this method is O(N log N) and it is much love. than a simple correlation esimation when the length of signal is long.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2005.11a
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• pp.249-252
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• 2005

본 논문에서는 자동차를 운전 시에 운전자의 얼굴과 눈의 영역을 자동으로 검출하고 눈동자를 추적하여 운전자의 졸음 여부를 판단하는 효과적인 시스템 구현방법을 제안한다. 복잡한 배경에서 얼굴과 눈을 검출하는 방법은 Haar-like feature의 원리를 이용하고 졸음운전으로 판단하는 방법은 눈동자 영역의 특성과 눈동자의 검출 유무, 움직임 등의 인식을 통하여 졸음운전 경보시스템의 실용화에 대한 가능성을 확인한다.

• ETRI Journal
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• v.30 no.2
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• pp.338-340
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• 2008

In this letter, we propose a novel approach to detecting and tracking apartment buildings for the development of a video-based navigation system that provides augmented reality representation of guidance information on live video sequences. For this, we propose a building detector and tracker. The detector is based on the AdaBoost classifier followed by hierarchical clustering. The classifier uses modified Haar-like features as the primitives. The tracker is a motion-adjusted tracker based on pyramid implementation of the Lukas-Kanade tracker, which periodically confirms and consistently adjusts the tracking region. Experiments show that the proposed approach yields robust and reliable results and is far superior to conventional approaches.

• Journal of Multimedia Information System
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• v.5 no.3
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• pp.189-194
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• 2018

In this paper, we propose the drowsiness detection method for car driver. This paper determines whether or not the driver's eyes are closed using the depth and infrared videos. The proposed method has the advantage to detect drowsiness without being affected by illumination. The proposed method detects a face in the depth picture by using the fact that the nose is closest to the camera. The driver's eyes are detected by using the extraction of harr-like feature within the detected face region. This method considers to be drowsiness if eyes are closed for a certain period of time. Simulation results show the drowsiness detection performance for the proposed method.

• Journal of Electrical Engineering and information Science
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• v.3 no.3
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• pp.348-354
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• 1998

The measured equation of invariance (MEI) method was introduced as a way to determine the electromagnetic fields scattered from discrete objects. Unlike more traditional numerical methods, MEI method over conventional methods over conventional methods are very substantial. In this work, Haar wavelets are applied to the measured equation of invariance (MEI) to solve two-dimensional scattering problem. We refer to "MEI method with wavelets" as "Wavelet MEI method". The proposed method leads to a significant saving in the CPU time compared to the MEI method that does not use wavelets as metrons. The results presented in this work promise that the Wavelet MEI method can give an accurate result quickly. We believe it is the first time that wavelets have been applied in conjunction with the MEI method to solve this scattering problem.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.2
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• pp.130-137
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• 2006

In this paper, we propose a method of selecting new types of rectangle features that are suitable for facial expression recognition. The basic concept in this paper is similar to Viola's approach, which is used for face detection. Instead of previous Haar-like features we choose rectangle features for facial expression recognition among all possible rectangle types in a 3${\times}$3 matrix form using the AdaBoost algorithm. The facial expression recognition system constituted with the proposed rectangle features is also compared to that with previous rectangle features with regard to its capacity. The simulation and experimental results show that the proposed approach has better performance in facial expression recognition.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.5
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• pp.390-395
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• 2000

We present a fingerprint identification algorithm using the wavelet transform and correlation. The wavelet transform is used because of its simple operation to extract fingerprint minutiaes features for fingerprint classification. We perform the rowwise 1-D wavelet transform for a $256\times256$ fingerprint image to get a $1\times256$ column vector using the Haar wavelet and repeat 1-D wavelet transform for a 1$\times$256 column vector to get a $1\times4$ feature vector. Using PNN(Probabilistic Neural Network), we select the possible candidates from the stored feature vectors for fingerprint images. For those candidates, we compute the correlation between the input binary image and the target binary image to find the most similar fingerprint image. The proposed algorithm may be the key to a low cost fingerprint identification system that can be operated on a small computer because it does not need a large memory size and much computation.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2008.04a
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• pp.201-204
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• 2008

머리전달함수(HRTF)가 정확하더라도 사람의 얼굴이 움직이게 되면 실제 머리전달함수와 미리 측정한 머리전달 함수가 달라져 입체음향 시스템의 성능이 저하되므로 정확한 얼굴의 회전각이 요구된다. 따라서 본 논문에서는 정확한 머리전달함수의 입력을 위해 사람 얼굴의 회전각을 추정하고자 한다. 제안하는 알고리즘은 먼저 Haar-like 특징을 이용하여 얼굴을 검출한 후 전처리 작업을 통해 눈의 바깥쪽 경계면과 안쪽 경계면을 검출한다. 그리고 검출된 두 개의 경계면의 비를 이용하여 얼굴의 회전각을 추정한다. 제안하는 알고리즘은 기존에 방법들에 비해 적용 범위가 넓음을 실험을 통해 알 수 있었다.

• Proceedings of the KOSOMBE Conference
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• v.1997 no.11
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• pp.99-102
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• 1997

A neural spike sorting technique has been developed that also has the capability of template learning. A system of software has been written that first obtains the templates by learning, and then performs the sorting of the spikes into single units. The spike sorting can be done in real time. The template learning consists of spike detection based on the discrete Haar transform (DHT), feature extraction by clustering of spike amplitude and duration, classification based on rms error, and fabrication of templates. The developed algorithms can be implemented into real time systems using digital signal processors.