Comparing two methods of object detection in autonomous vehicle

D. Rosas-Miranda, V. Ponomaryov, A. Palacios-Enriquez
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引用次数: 1

Abstract

Autonomous obstacle avoidance in mobile robots has been an active field in image processing and control theory. In this paper, we propose and evaluate two methods for multiple objects detection for a mobile robot in outdoor. The first method uses a block matching algorithm to obtain a disparity map and SURF features detector. The second method uses a semi-global stereo vision environment. Both methods are tested during detecting pedestrian, boxes and cones using a video sequence in validation of a robot.
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自动驾驶汽车中两种目标检测方法的比较
移动机器人的自主避障一直是图像处理和控制理论研究的热点。本文提出并评价了户外移动机器人多目标检测的两种方法。第一种方法使用块匹配算法获得视差图和SURF特征检测器。第二种方法采用半全局立体视觉环境。这两种方法都在检测行人、箱子和锥体的过程中进行了测试,使用视频序列来验证机器人。
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