Study of Video Semantic-concept Classifier with Multi-normal Distribution Attribute
具有多峰正态分布属性的视频语义分类研究

Attributes with multi-normal distribution are common in classifier design for video-semantic concept.In this case,a model assuming that the value of attributes for each class is normally distributed with some mean will lead to poor classification performance.In the paper,an approach based on fixed-length combination partition algorithm(FLC- PA)is presented in the partition of attribute value-field.Leave-one-out cross-validation(LOOCV)is used to estimate classifier error.In addition,the detail of classifier design about multi-normality distribution attribute is given.The re- suit of experiment indicate the method could reduce classifier error and improve classifier performance.