首页> 外文会议>IASTED international conference on Signal processing, pattern recognition, and applications >ROAD PLANE DETECTION USING DIFFERENTIAL HOMOGRAPHY ESTIMATED BY PAIR FEATURE MATCHING OF LOCAL REGIONS
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ROAD PLANE DETECTION USING DIFFERENTIAL HOMOGRAPHY ESTIMATED BY PAIR FEATURE MATCHING OF LOCAL REGIONS

机译:使用当地地区的对特征匹配估计的差分配合的道路平面检测

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This paper presents a novel algorithm for road plane detection from an on-board camera. The algorithm employs the temporal difference of homography matrix, which is termed differential homography, caused by camera motion. Differential homography is estimated from optical flows of road plane regions, while using RANSAC algorithm to extract the majority optical flows. Since differential homography is estimated using the relationship between the image coordinate (location in an image) and the flows at the locations in an image. The proposed algorithm does not require the estimation of the homography matrix itself. Therefore, the proposed algorithm can be applied without calibration. The proposed algorithm effectively detect the optical flows from road region with using the pixel-pair feature matching. The algorithm is applied to the city traffic images distributed by UCL, and its average road detection ratio is found to be 75.6%. It is also applied to the previously collected suburban traffic images. A suitable detection result is obtained.
机译:本文提出了一种从车载相机进行道路平面检测的新算法。该算法采用了由相机运动引起的定位矩阵的时间差异,该矩阵被称为差分相同。差分定位估计来自道路平面区域的光学流量,同时使用RANSAC算法提取大多数光学流。由于使用图像坐标(图像中的位置)之间的关系和图像中的位置处的流程来估计差异相同。所提出的算法不需要估计相同矩阵本身。因此,可以在不校准的情况下应用所提出的算法。使用像素对特征匹配,所提出的算法有效地检测来自道路区域的光学流。该算法应用于由UCL分布的城市业务图像,并且其平均道路检测比率为75.6%。它也应用于先前收集的郊区交通图像。获得合适的检测结果。

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