CAJ | 학술논문

为了实现目标的快速检测,提出了一种新的基于拉格朗日支持向量机(L-SVM)的线I}生级联式分类器的构造方法.该方法首先根据样本的几何分布,用迭代的方式把负样本分成若干部分与正样本线性可分的样本;然后用L-SVM对这些正负样本进行分类,得到若干个线性分类器;最后,将这些线性分类器顺次组合,构成级联分类器.实验表明,与经典非线性SVM分类器相比,这种分类器在保持SVM较强泛化性能的优点的同时,在检测效率方面更是具有明显的优势.
위료실현목표적쾌속검측,제출료일충신적기우랍격랑일지지향량궤(L-SVM)적선I}생급련식분류기적구조방법.해방법수선근거양본적궤하분포,용질대적방식파부양본분성약간부분여정양본선성가분적양본;연후용L-SVM대저사정부양본진행분류,득도약간개선성분류기;최후,장저사선성분류기순차조합,구성급련분류기.실험표명,여경전비선성SVM분류기상비,저충분류기재보지SVM교강범화성능적우점적동시,재검측효솔방면경시구유명현적우세.
To detect objects quickly,a new method is presented to construct a cascade of linear classifiers with L-SVM(La-grangian Support Vector Machine,L-SVM).At first,the negative data is divided into several parts accumulatively according to the geometric distribution of the training data.Here,every part of negative data is separable with the positive data;Second,L-SVM is used to obtain the linear classifiers between every part of negative data and positive data;At last,the linear classifiers are com-bined to construct a cascade detector.The experiments show that this method enjoys good generalization capacity and much fast speed compared with the traditional SVMs.