• Title/Summary/Keyword: vanishing points

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Inside Wall Frame Detection Method Based on Single Image (단일이미지에 기반한 내벽구조 검출 방법)

  • Jeong, Do-Wook;Jung, Sung-Gi;Choi, Hyung-Il
    • Journal of Internet Computing and Services
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    • v.18 no.1
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    • pp.43-50
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    • 2017
  • In this paper, we are proposing improved vanishing points detection and segments labeling methods for inside wall frame detection from indoor image of a piece of having a colour RGB. A lot of research related to recognizing the frame of artificial structures from the image is being performed due to increase in demand for AR technology. But detect the inside wall frame in indoor images have many objects that caused the occlusion is still a difficult issue. Inner wall frame detection methods are usually segment labeling methods and detect vanishing point methods are used together. In order to improve the vanishing point detection method we proposed using inner wall orthogonality which forms the cube. Also we proposed labeling method using tree based learning and superpixel based segmentation method for labelingthe segments in indoor images. Finally, in experiments have shown improved results about inside wall frame detection according to our methods.

Method for Road Vanishing Point Detection Using DNN and Hog Feature (DNN과 HoG Feature를 이용한 도로 소실점 검출 방법)

  • Yoon, Dae-Eun;Choi, Hyung-Il
    • The Journal of the Korea Contents Association
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    • v.19 no.1
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    • pp.125-131
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    • 2019
  • A vanishing point is a point on an image to which parallel lines projected from a real space gather. A vanishing point in a road space provides important spatial information. It is possible to improve the position of an extracted lane or generate a depth map image using a vanishing point in the road space. In this paper, we propose a method of detecting vanishing points on images taken from a vehicle's point of view using Deep Neural Network (DNN) and Histogram of Oriented Gradient (HoG). The proposed algorithm is divided into a HoG feature extraction step, in which the edge direction is extracted by dividing an image into blocks, a DNN learning step, and a test step. In the learning stage, learning is performed using 2,300 road images taken from a vehicle's point of views. In the test phase, the efficiency of the proposed algorithm using the Normalized Euclidean Distance (NormDist) method is measured.

3D Reconstruction using vanishing points (소실점을 이용한 3차원 재구성)

  • Kim, Sang-Hoon;Choi, Jong-Soo;Kim, Tae-Eun
    • The KIPS Transactions:PartB
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    • v.10B no.5
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    • pp.515-520
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    • 2003
  • This paper proposes a calibration method from two images. Camera calibration is necessarily required to obtain 3D Information from 2D images. Previous works to accomplish the camera calibration needed the calibration object or required more than three images to calculate the Kruppa equation, however, we use the geometric constraints of parallelism and orthogonality can be easily presented in man-made scenes. The task of it is to obtain intrinsic and extrinsic camera parameters. The intrinsic parameters are evaluated from vanishing points and then the extrinsic parameters which are consisted of rotation matrix and translation vector of the camera are estimated from corresponding points of two views. From the calibrated parameters, we can recover the projection matrices for each view point. These projection matrices are used to recover 3D information of the scene and can be used to visualize new viewpoints.

Geometrical Building Analysis for Outdoor Environment Understanding of Autonomous Navigation Robot (자율주행 로봇의 외부환경 이해를 위한 기하학적인 빌딩 분석)

  • Kim, Dae-Nyeon;Trinh, Hoang-Hon;Jo, Kang-Hyun
    • Journal of Institute of Control, Robotics and Systems
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    • v.16 no.3
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    • pp.277-285
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    • 2010
  • This paper describes an approach to analyze geometrical information of building images for understanding outdoor environment of autonomous navigation robot. Line segments and color information are used to classily a building with the other objects such as sky, trees, and roads. The line segments and their two neighboring regions are extracted from detected edges in image. The model of line segment (MLS) consists of color information of neighbor regions. This model rules out the line segments of non-building face. A building face converges into dominant vanishing points (DVPs) which include one vertical point and one of five horizontal points in maximum. The intersection of vertical and horizontal lines creates a facet of building. The geometrical characteristics such as the center coordinates, area, aspect ratio and aligned coexistence are used for extracting the windows in the building facet. In experiments, 150 building faces and 1607 windows were detected from the database of outdoor environment. We found that this result shows 94.46% detection rate. These experimental images were all taken in Ulsan metropolitan city in Korea under difference of viewpoints, daytime, camera system and weather condition.

Semi-automatic 3D Building Reconstruction from Uncalibrated Images (비교정 영상에서의 반자동 3차원 건물 모델링)

  • Jang, Kyung-Ho;Jang, Jae-Seok;Lee, Seok-Jun;Jung, Soon-Ki
    • Journal of Korea Multimedia Society
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    • v.12 no.9
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    • pp.1217-1232
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    • 2009
  • In this paper, we propose a semi-automatic 3D building reconstruction method using uncalibrated images which includes the facade of target building. First, we extract feature points in all images and find corresponding points between each pair of images. Second, we extract lines on each image and estimate the vanishing points. Extracted lines are grouped with respect to their corresponding vanishing points. The adjacency graph is used to organize the image sequence based on the number of corresponding points between image pairs and camera calibration is performed. The initial solid model can be generated by some user interactions using grouped lines and camera pose information. From initial solid model, a detailed building model is reconstructed by a combination of predefined basic Euler operators on half-edge data structure. Automatically computed geometric information is visualized to help user's interaction during the detail modeling process. The proposed system allow the user to get a 3D building model with less user interaction by augmenting various automatically generated geometric information.

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Deciding the Direction for Autonomous Navigation of the Powered Wheelchair with Vanishing Points (소실점 처리를 이용한 전동 휠체어의 자율 주행 판단)

  • Park, Choong-Shik;Kim, Jae-Hong;Lee, Bong-Keun;Koo, Min-Jeong;Jang, Se-In;Lee, Han-Lim;Kim, Kwang-Baek;Kang, Hyun-Seuk;Cha, Myoung-Seok
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2009.01a
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    • pp.55-60
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    • 2009
  • 본 논문은 복도 영상에서 소실점만으로 방향을 판단하여 주행하는 방법을 제시한다. 허프 변환을 이용하여 추출된 선 성분으로 소실점을 구하고 다양한 경우를 고려하여 회전과 주행 방향을 판단한다. 제안된 방법으로 전동 휠체어를 이용하여 자율 주행을 확인하였다.

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The Corridor Scene Analysis for a Motorized Wheelchair's Automatic Locomotion (전동휠체어 자동 주행을 위한 복도영상 해석)

  • Moon, Cheol-Hong;Han, Yeong-Hwan;Hong, Seung-Hong
    • Journal of Biomedical Engineering Research
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    • v.15 no.1
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    • pp.27-34
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    • 1994
  • In this paper. a way to analysis a corridor scene for a vehicle's automatic locomotion is presented In general, it's necessary for a vision system of vehicles to identify its positions in given environments. The suggested algorithm is to decide base lines of a corridor image using the vanishing point finding. Feature points are extracted on the base line using a base line extraction tree. This algorithm is suitable for a motorized wheelchair's self locomotion in a building.

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The course estimation of vehicle using vanishing point and obstacle detection (무한원점을 이용한 주행방향 추정과 장애물 검출)

  • 정준익;최성구;노도환
    • Journal of the Korean Institute of Telematics and Electronics S
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    • v.34S no.11
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    • pp.126-137
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    • 1997
  • This paper describes the algorithm which can estimate road following direction and deetect obstacle using a monocular vision system. This algorithm can estimate the course of vehicle using the vanishing point properties and detect obstacle by statistical method. The proposed algorithm is composed of four steps, which are lane prediction, lane extraction, road following parameter estimation and obstacle detection. It is designed for high processing speed and high accuracy. The former is achieved by a small area named sub-windown in lane existence area, the later is realized by using connected edge points of lane. We would like to present that the new mehod can detect obstacle using the simple statistical method. The paracticalities of the processing speed, the accuracy of the algorithm and proposing obstacle detection method, have been justified through the experiment applied VTR image of the real road to the algorithm.

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The Real-Time Height Measurement through a Geometry Information and 0bject Extraction (기하학 정보와 객체 추출을 통한 실시간 높이 측정)

  • Kim Jong Su;Kim Tae Yong;Choi Jong Soo
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.29 no.12C
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    • pp.1652-1659
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    • 2004
  • In this paper, we propose the algorithm that automatically measures the height of the object to move on the base plane by using the geometric information. To extract a moving object from real-time images creates the background image and each pixel is modeled by the three values. The extracted region is represented by cardboard model and calculates the coordinate center in the each part. The top and bottom point of an object are extracted by the calculated coordinate center and an iterative computation. The two points, top and bottom, are used for measuring the height. Given the vanishing line of the ground plane, the vertical vanishing point, and at least one reference height in the scene; then the height of any point from the ground may be computed by specifying the image of the point and the image of the vertical intersection with the ground plane at that point. Through a confidence valuation of the height to be measured, we confirmed similar actual height and result in the simulation experiment.

Correspondence Search Algorithm for Feature Tracking with Incomplete Trajectories

  • Jeong, Jong-Myeon;Moon, young-Shik
    • Proceedings of the IEEK Conference
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    • 2000.07b
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    • pp.803-806
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    • 2000
  • The correspondence problem is known to be difficult to solve because false positives and false negatives almost always exist in real image sequences. In this paper, we propose a robust feature tracking algorithm considering incomplete trajectories such as entering and/or vanishing trajectories. We solve the correspondence problem as the optimal graph search problem, by considering false feature points and by properly reflecting motion characteristics. The proposed algorithm finds a local optimal correspondence so that the effect of false feature points can be minimized in the decision process. The time complexity of the proposed graph search algorithm is given by O(mn) in the best case and O(m$^2$n) in the worst case, where m and n are the number of feature points in two consecutive frames. The proposed algorithm can find trajectories correctly and robustly, which has been shown by experimental results.

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