• Title/Summary/Keyword: 역투시변환

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역투시 변환을 이용한 스테레오 비젼 알고리즘에 관한 연구

  • 조용철;조형석
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 2001.10a
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    • pp.209-213
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    • 2001
  • 본 논문에서 계산구현 방법이 간단하고, 물체에 대한 정보 획득 측면에서 효율성을 기할 수 있는 스테레오 비전 알고리즘이 제시된다. 이는 공간을 미리 계획된 다단 평면상에 놓이는 물체점들을 역투시 변환에 의한 영상의 재투영 과정과 영상면 상관법에 의해서 평면상의 정보를 순차적으로 구한다. 제안된 알고리즘은 이동로보트의 장애물 감지작업에 적용하여 그 효율성을 보인다.

A Robust Real-Time Lane Detection for Sloping Roads (경사진 도로 환경에서도 강인한 실시간 차선 검출방법)

  • Heo, Hwan;Han, Gi-Tae
    • KIPS Transactions on Software and Data Engineering
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    • v.2 no.6
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    • pp.413-422
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    • 2013
  • In this paper, we propose a novel method for real-time lane detection that is robust for inclined roads and not require a camera parameter, the Inverse Perspective Transform of the image, and the proposed lane filter. After finding the vanishing point from the start frame of the image and storing the region surrounding the vanishing point as the Template Area(TA), our method predict the lanes by scanning toward the lower part from the vanishing point of the image and obtain the image removed the perspective effect using the Inverse Perspective Transform coefficients extracted based on the predicted lanes. To robustly determine lanes on inclined roads, the region surrounding the vanishing point is set up as the template area (TA), and, by recalculating the vanishing point by tracing the area similar to the TA (SA) in the input image through template matching, it responds to the changes on the road conditions. The proposed method for a more robust lane detection method for inclined roads is a lane detection method by applying a lane detection filter on an image removed of the perspective effect. Through this method, the processing region is reduced and the processing procedure is simplified to produce a satisfactory lane detection result of about 40 frames per second.

A Curve Lane Detection Method using Lane Variation Vector and Cardinal Spline (차선 변화벡터와 카디널 스플라인을 이용한 곡선 차선 검출방법)

  • Heo, Hwan;Han, Gi-Tae
    • KIPS Transactions on Software and Data Engineering
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    • v.3 no.7
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    • pp.277-284
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    • 2014
  • The detection method of curves for the lanes which is powerful for the variation by utilizing the lane variation vector and cardinal spline on the inverse perspective transformation screen images which do not required the camera parameters are suggested in this paper. This method detects the lane area by setting the expected lane area in the s frame and next s+1 frame where the inverse perspective transformation and entire process of the lane filter are adapted, and expects the points of lane location in the next frames with the lane variation vector calculation from the detected lane areas. The scan area is set from the nextly expected lane position and new lane positions are detected within these areas, and the lane variation vectors are renewed with the detected lane position and the lanes are detected with application of cardinal spline for the control points inside the lane areas. The suggested method is a powerful method for curved lane detection, but it was adopted to the linear lanes too. It showed an excellent lane detection speed of about 20ms in processing a frame.

Camera Parameter Extraction Method for Virtual Studio Applications by Tracking the Location of TV Camera (가상스튜디오에서 실사 TV 카메라의 3-D 기준 좌표와 추적 영상을 이용한 카메라 파라메타 추출 방법)

  • 한기태;김회율
    • Journal of Broadcast Engineering
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    • v.4 no.2
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    • pp.176-186
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    • 1999
  • In order to produce an image that lends realism to audience in the virtual studio system. it is important to synchronize precisely between foreground objects and background image provided by computer graphics. In this paper, we propose a method of camera parameter extraction for the synchronization by tracking the pose of TV camera. We derive an equation for extracting camera parameters from inverse perspective equations for tracking the pose of the camera and 3-D transformation between base coordinates and estimated coordinates. We show the validity of the proposed method in terms of the accuracy ratio between the parameters computed from the equation and the real parameters that applied to a TV camera.

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