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首页> 外文期刊>Computers and Electronics in Agriculture >Human detection for a robot tractor using omni-directional stereo vision.
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Human detection for a robot tractor using omni-directional stereo vision.

机译:使用全向立体视觉对机器人拖拉机进行人体检测。

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摘要

It is critical to detect and identify obstacles for safe operation of robot tractors. This study focused on human detection using an omni-directional stereo vision (OSV). The Lucas-Kanade optical flow detection method was used to detect human in a panoramic image. A 3D panoramic image that was reconstructed from stereo rectified images using the sum of squared differences (SSDs) method was used to locate the position of a human. To evaluate the performance of the developed human detection method, two RTK-GPSs were used to investigate the accuracy of the detection method under stationary and motion conditions of a robot tractor. The results of field experiments indicated that a human could be detected successfully under both given conditions in the daytime. The RMS error of measured distance was less than half a meter compared with the reference distance measured by the RTK-GPSs.
机译:检测和识别障碍物对于机器人拖拉机的安全运行至关重要。这项研究的重点是使用全向立体视觉(OSV)进行人体检测。 Lucas-Kanade光流检测方法用于检测全景图像中的人。使用平方差总和(SSD)方法从立体校正图像重建的3D全景图像用于定位人的位置。为了评估开发的人体检测方法的性能,使用了两个RTK-GPS来研究在机器人拖拉机的静止和运动条件下检测方法的准确性。野外实验的结果表明,在白天在两种给定条件下都可以成功检测到人类。与RTK-GPS测得的参考距离相比,测得距离的RMS误差小于半米。

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