• 제목/요약/키워드: Rotation Angle Detection

검색결과 64건 처리시간 0.026초

Rotation Invariant Face Detection Using HOG and Polar Coordinate Transform

  • Jang, Kyung-Shik
    • 한국컴퓨터정보학회논문지
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    • 제26권11호
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    • pp.85-92
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    • 2021
  • 이 논문에서는 회전각도에 무관하게 회전 얼굴과 회전각도를 효과적으로 검출하는 방법이 제안되었다. 회전된 얼굴 검출은 회전에 따른 얼굴 외형의 큰 변화로 인해 어려운 분야이다. 제안한 극좌표계 변환 방법은 회전 각도와 무관하게 얼굴 구성요소들의 위치 정보가 유지되기 때문에 회전으로 인한 얼굴의 외형 변화가 없게 된다. 이에 따라 회전이 없는 정면 얼굴 검출에 사용되지만 회전에 민감한 특성을 갖는 HOG와 같은 특징들이 회전얼굴을 검출하는 과정에서 효과적으로 사용될 수 있다. 극좌표계 변환된 영상에서 얻은 HOG 특징을 SVM을 이용하여 학습하고 회전 얼굴을 검출하였다. 학습 데이터는 회전이 없는 정면 얼굴 영상만을 사용하였다. 3600개 회전 얼굴 영상에 대한 실험 결과 97.94 %의 회전각도 검출률을 얻었다. 또한, 다수의 회전 얼굴이 포함된 배경이 있는 영상들에서 회전 얼굴들의 위치와 회전 각도를 정확하게 검출하였다.

크로스토크 제거를 위한 얼굴 방위각 검출 기법 (Detection Method of Face Rotation Angle for Crosstalk Cancellation)

  • 한상일;차형태
    • 한국지능시스템학회논문지
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    • 제17권1호
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    • pp.58-65
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    • 2007
  • 2채널 방식을 이용하는 입체 음향 구현 방법은 멀티채널 방식에 비해 비용의 감소 효과 및 설치가 쉽다는 장점이 있으나 크로스토크(crosstalk)를 제거하는 것이 어려운 문제이다. 크로스토크를 제거하기 위해서는 머리의 위치를 정확하게 추정하는 것이 필수적이다. 따라서 본 논문에서는 2채널 방식에서 3차원 입체 음향을 구현하기 위해 얼굴의 방향을 추정하기 위한 알고리즘을 제시한다. 제안하는 알고리즘은 Haar-like 특징을 이용하여 얼굴을 검출하고 전처리 작업과 수학적 형태학을 이용한 두 눈의 위치를 검출하는 알고리즘을 이용, 얼굴이 향하고 있는 방위각을 검출한다. 본 논문에서 제안하는 알고리즘은 기존의 제안되어진 방법들에 비해 적용 범위가 더 넓으며, 얼굴 방위각이 매우 안정적으로 검출됨을 실험을 통해 알 수 있었다.

Real-Time Rotation-Invariant Face Detection Using Combined Depth Estimation and Ellipse Fitting

  • Kim, Daehee;Lee, Seungwon;Kim, Dongmin
    • IEIE Transactions on Smart Processing and Computing
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    • 제1권2호
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    • pp.73-77
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    • 2012
  • This paper reports a combined depth- and model-based face detection and tracking approach. The proposed algorithm consists of four functional modules; i) color-based candidate region extraction, ii) generation of the depth histogram for handling occlusion, iii) rotation-invariant face region detection using ellipse fitting, and iv) face tracking based on motion prediction. This technique solved the occlusion problem under complicated environment by detecting the face candidate region based on the depth-based histogram and skin colors. The angle of rotation was estimated by the ellipse fitting method in the detected candidate regions. The face region was finally determined by inversely rotating the candidate regions by the estimated angle using Haar-like features that were robustly trained robustly by the frontal face.

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A Novel Implementation of Rotation Detection Algorithm using a Polar Representation of Extreme Contour Point based on Sobel Edge

  • Han, Dong-Seok;Kim, Hi-Seok
    • JSTS:Journal of Semiconductor Technology and Science
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    • 제16권6호
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    • pp.800-807
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    • 2016
  • We propose a fast algorithm using Extreme Contour Point (ECP) to detect the angle of rotated images, is implemented by rotation feature of one covered frame image that can be applied to correct the rotated images like in image processing for real time applications, while CORDIC is inefficient to calculate various points like high definition image since it is only possible to detect rotated angle between one point and the other point. The two advantages of this algorithm, namely compatibility to images in preprocessing by using Sobel edge process for pattern recognition. While the other one is its simplicity for rotated angle detection with cyclic shift of two $1{\times}n$ matrix set without complexity in calculation compared with CORDIC algorithm. In ECP, the edge features of the sample image of gray scale were determined using the Sobel Edge Process. Then, it was subjected to binary code conversion of 0 or 1 with circular boundary to constitute the rotation in invariant conditions. The results were extracted to extreme points of the binary image. Its components expressed not just only the features of angle ${\theta}$ but also the square of radius $r^2$ from the origin of the image. The detected angle of this algorithm is limited only to an angle below 10 degrees but it is appropriate for real time application because it can process a 200 degree with an assumption 20 frames per second. ECP algorithm has an O ($n^2$) in Big O notation that improves the execution time about 7 times the performance if CORDIC algorithm is used.

Inductive Sensor and Target Board Design for Accurate Rotation Angle Detection

  • Hwang, Jae-Jeong;Moon, Joon
    • International Journal of Internet, Broadcasting and Communication
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    • 제9권1호
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    • pp.64-70
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    • 2017
  • In the commercial building such as huge enterprise building, more accurate operation of the center-controlled roller blind. We design, in this work, the target disc that its shape is nonlinearly changing and the sensor coils that are differentially arranged. The performance shows less than 1% accuracy when it is implemented in the roller blind.

특징점 추출을 통한 HMD 회전각측정 알고리즘 개발 (Development of a rotation angle estimation algorithm of HMD using feature points extraction)

  • 노영식;김철희;윤원준;윤유경
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2009년도 정보 및 제어 심포지움 논문집
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    • pp.360-362
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    • 2009
  • In this paper, we studied for the real-time azimuthal measurement of HMD(Head Mounted Display) using the feature points detection to control the tele-operated vision system on the mobile robot. To give the sense of presence to the tele-operator, we used a HMD to display the remote scene, measured the rotation angle of the HMD on a real time basis, and transmitted the measured rotation angles to the mobile robot controller to synchronize the pan-tilt angles of remote camera with the HMD. In this paper, we suggest an algorithm for the real-time estimation of the HMD rotation angles using feature points extraction from pc-camera image.

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얼굴 요소의 특징을 이용한 얼굴 방위각 검출 기법 (Detection Method of Face Rotation Angle Using Facial Features)

  • 한상일;구교식;서보국;차형태
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2007년도 하계종합학술대회 논문집
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    • pp.385-386
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    • 2007
  • In this paper, we present a detection method of facial angle using facial features. First, it finds face image using haar-like feature. After that, it finds eyes and lip in need of compute of face rotation angle. Next, it makes a triangle by using the facial features and computes the inside angle. As a result of experiment on various face images, the proposed method improves the efficiency much better than the conventional methods below $40^{\circ}$.

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Analogical Face Generation based on Feature Points

  • Yoon, Andy Kyung-yong;Park, Ki-cheul;Oh, Duck-kyo;Cho, Hye-young;Jang, Jung-hyuk
    • Journal of Multimedia Information System
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    • 제6권1호
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    • pp.15-22
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    • 2019
  • There are many ways to perform face recognition. The first step of face recognition is the face detection step. If the face is not found in the first step, the face recognition fails. Face detection research has many difficulties because it can be varied according to face size change, left and right rotation and up and down rotation, side face and front face, facial expression, and light condition. In this study, facial features are extracted and the extracted features are geometrically reconstructed in order to improve face recognition rate in extracted face region. Also, it is aimed to adjust face angle using reconstructed facial feature vector, and to improve recognition rate for each face angle. In the recognition attempt using the result after the geometric reconstruction, both the up and down and the left and right facial angles have improved recognition performance.

문서 영상의 영역 분류와 회전각 검출 (A Block Classification and Rotation Angle Extraction for Document Image)

  • 모문정;김욱현
    • 정보처리학회논문지B
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    • 제9B권4호
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    • pp.509-516
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    • 2002
  • 본 논문에서는 그림, 글자, 표, 직선 등과 같은 다양한 정보를 포함하는 문서 영상 인식에 대한 효율적인 알고리즘을 제안한다. 이 시스템은 문서영상의 기울짐을 보정하기 위한 회전각검출 단계, 불필요한 배경영역을 제거하는 단계, 문서영상에 내재된 각 구성요소를 검출하는 분류 단계로 구성된다. 알고리즘은 문서의 기울어짐에 의해서 발생되는 오류를 최소화하기 위한 회전각 검출과정과 검출된 회전각을 기반으로 문서를 보정하는 전처리단계를 수행한다. 입력된 문서영상의 수평성분과 수직성분만을 이용하여 회전각을 검출하고, 문서의 구성요소 검출과정에서 불필요한 배경영역을 제거함으로써 계산시간을 최소화하였다. 그리고 영상에 내재된 그림영역, 글자영역, 표영역, 직선영역 둥의 다양한 구성요소를 분류한다. 제안한 문서 인식 시스템의 성능 평가를 위해서 다양한 문서영상에 제안한 방법을 적용하고 성공적인 결과를 보인다.

회전각 검출용 3축 수직 Hall 센서 (Three Branches Vertical Hall Sensor for Rotation Angle Detection)

  • 이지연;남태철
    • 한국전기전자재료학회논문지
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    • 제18권9호
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    • pp.840-845
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    • 2005
  • A three branches vortical Hall sensor for detecting rotation angle of brushless motor has fabricated. The sensor is constructed three branches of $150{\mu}m$ width and $300{\mu}m$ distance from central electrode to Hall electrode. Each branch has one Hall output and one Hall input. The central electrode acts as common driving input. According to rotation angle change of brushless motor, sensor gives three position signals phase shifted by $120^{\circ}$. The sensitivity of sensor is 200V/A$\cdot$T at magnetic field of 0.1 T and constant driving current of 1mA. It has also showed three sine waves of Hall output voltages with $120^{\circ}$ phase over one motor rotation. The noise can limit sensor's resolution. We have measured sensor's noise characteristics. The detectable minimum magnetic field is $20{\mu}T$ at driving current 1mA, measured frequency 1 kHz and bandwidth$({\Delta}f)$ of 1Hz.