%0 Journal Article
%T The conversion of histograms of oriented gradient in different vision-angle and rotation-angle<br>视角和旋转角变化时梯度方向直方图的转换
%A LIU Qing
%A WU Zhi-gang
%A GUO Jian-ming
%A LI Long-li
%A <br>刘清
%A 吴志刚
%A 郭建明
%A 李龙利
%J 控制理论与应用
%D 2010
%I 
%X 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.
%K object-detection
%K vision-angle
%K rotation-angle
%K histograms of oriented gradient
%K SVM<br>目标检测
%K 视角
%K 旋转角
%K 梯度方向直方图HOG
%K 支持向量机
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=970898A57DFC021F93AB51667BAED7F7&aid=B1A0CE245056E70D7D090CB4E6BBA5EB&yid=140ECF96957D60B2&vid=DB817633AA4F79B9&iid=9CF7A0430CBB2DFD&sid=3ED1EAB217774597&eid=F82BA45C3E48287D&journal_id=1000-8152&journal_name=控制理论与应用&referenced_num=0&reference_num=7