| 引用本文: | 刘清,吴志刚,郭建明,李龙利.视角和旋转角变化时梯度方向直方图的转换[J].控制理论与应用,2010,27(9):1269~1272.[点击复制] |
| LIU Qing,WU Zhi-gang,GUO Jian-ming,LI Long-li.The conversion of histograms of oriented gradient in different vision-angle and rotation-angle[J].Control Theory & Applications,2010,27(9):1269~1272.[点击复制] |
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| 视角和旋转角变化时梯度方向直方图的转换 |
| The conversion of histograms of oriented gradient in different vision-angle and rotation-angle |
| 摘要点击 2355 全文点击 1782 投稿时间：2009-01-05 修订日期：2009-11-13 |
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| DOI编号 |
| 2010,27(9):1269-1272 |
| 中文关键词 目标检测 视角 旋转角 梯度方向直方图HOG 支持向量机 |
| 英文关键词 object-detection vision-angle rotation-angle histograms of oriented gradient SVM |
| 基金项目 高等学校博士学科点专项科研基金资助(20060497017). |
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| 中文摘要 |
| 使用梯度方向直方图(HOG)来检测目标, 需要大量的, 有代表性的样本来训练分类器. 一个目标的HOG, 其特征在不同的摄像机视角和不同的光轴旋转角下, 并不相同. 因此, 使用不同视角下的混合样本集来训练分类器时,目标检测的准确率受到样本噪声的影响将会降低. 基于摄像机成像的基本原理, 提出了一种转换算法, 可以把一个样本在某个视角下的HOG特征转换成另一个视角下的HOG特征. 这样既降低了分类器训练时需要采集的正负样本数量, 又提高了支持向量机(SVM)分类的准确性, 从而提高了目标检测的准确性. 大量目标检测实验结果表明本文提出的算法是有效的. |
| 英文摘要 |
| In applying the histograms of oriented gradient(HOG) to detect an object, we need a great number of representative image samples to train the classifier. Since the HOG characteristic changes in different vision-angle and different rotation-angle, the detection accuracy will be decreased if images of different vision-angle or rotation-angle are used to train the classifier. By the imaging principle of the camera, we develop an algorithm for converting the HOG characteristic in one vision-angle and rotation-angle to the HOG characteristic in another vision-angle and rotation-angle. Thus, the required number of positive and negative samples for training the classifier is reduced and the classification accuracy of the support-vector-machines(SVM) is raised, eventually resulting in an increase in the object detection accuracy and robustness. Many object-detection experimental results show that this conversion algorithm is effective. This indicates that the proposed algorithm is an efficient tool for HOG-based object detection in practical engineering projects. |
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