• 제목/요약/키워드: Haar system

검색결과 139건 처리시간 0.021초

서비스 로봇을 위한 지시 물체 분할 방법 (Segmentation of Pointed Objects for Service Robots)

  • 김형오;김수환;김동환;박성기
    • 로봇학회논문지
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    • 제4권2호
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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.

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웨이블릿 변환을 이용한 시간 지연 추정법 (Time Delay Estimation using Wavelet Transform)

  • 김도형;박영진
    • 한국음향학회:학술대회논문집
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    • 한국음향학회 2000년도 하계학술발표대회 논문집 제19권 1호
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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.

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눈 검출 및 눈동자 추적 기반을 통한 졸음운전 경보 시스템 구현 (Implementation of Drowsiness Driving Warning System based on Eyes Detection and Pupi1 Tracking)

  • 민지홍;김정철;홍기천
    • 한국지능시스템학회:학술대회논문집
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    • 한국퍼지및지능시스템학회 2005년도 추계학술대회 학술발표 논문집 제15권 제2호
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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.

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Real-Time Apartment Building Detection and Tracking with AdaBoost Procedure and Motion-Adjusted Tracker

  • Hu, Yi;Jang, Dae-Sik;Park, Jeong-Ho;Cho, Seong-Ik;Lee, Chang-Woo
    • ETRI Journal
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    • 제30권2호
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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.

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Drowsiness Detection Method during Driving by using Infrared and Depth Pictures

  • You, Gang-chon;Park, Do-hyun;Kwon, Soon-kak
    • Journal of Multimedia Information System
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    • 제5권3호
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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.

The Application of Wavelets to Measured Equation of Invariance

  • Lee, Byunfji;Youngki Cho;Lee, Jaemin
    • Journal of Electrical Engineering and information Science
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    • 제3권3호
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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.

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실시간 얼굴 표정 인식을 위한 새로운 사각 특징 형태 선택기법 (New Rectangle Feature Type Selection for Real-time Facial Expression Recognition)

  • 김도형;안광호;정명진;정성욱
    • 제어로봇시스템학회논문지
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    • 제12권2호
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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.

웨이블릿변환과 상관관계를 이용한 지문의 분류 및 인식 (Fingerprint Classification and Identification Using Wavelet Transform and Correlation)

  • 이석원;남부희
    • 제어로봇시스템학회논문지
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    • 제6권5호
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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.

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입체 음향을 위한 개선된 얼굴 방위각 검출 (Improved Detection Method Face Rotation Angle for 3D Sound System)

  • 한상일;류일현;서보국;구교식;차형태
    • 한국지능시스템학회:학술대회논문집
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    • 한국지능시스템학회 2008년도 춘계학술대회 학술발표회 논문집
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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.

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학습 가능한 실시간 다단위 신경 신호의 분류에 관한 연구 (Classification of Multi-Unit Neural Action Potential by Template Learning)

  • 김상돌;김경환;김성준
    • 대한의용생체공학회:학술대회논문집
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    • 대한의용생체공학회 1997년도 추계학술대회
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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.

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