关键词: 训练样本, 样本分类, 边界样本, 支持向量机

Abstract:

Sample preparation is the basis of machine learning，which is directly related to the final performance of the algorithm for the object recognition.It is a resource-consuming task with trivialities.Thus，an automatic method of sample preparation is proposed，which includes two stages：coarse-sample preparation stage and fine-sample preparation stage.Coarse-sample preparation stage aims to collect all samples according to the current standard based on image segmentation algorithm；subsequently，fine-sample preparation selects the boundary samples from the coarse samples based on SVM to reduce the sample scale and ensure the high learning efficiency of machine learning.Applying this method to vehicle recognition，the experiment results demonstrate that the proposed method is effective and efficient and it has great value to be applied and popularized.

Key words: training sample, sample classification, boundary sample, Support Vector Machine（SVM）