湖南大学学报（自然科学版）2013，Vol.40Issue(8)：58-63,6.
基于协方差描述子和LogitBoost的交通场景图像分割
Segmentation of Traffic Scene Based on Covariance Descriptor and LogitBoost Classifier
摘要
Abstract
In order to overcome the drawback of traditional method directly using image features to classify images,which will produce the problems of feature redundancy and low accuracy,a new approach based on Covariance Descriptor and LogitBoost was proposed for the image segmentation of traffic scene.The motion and structure,texture and HOG features were extracted for segmenting image.Meanwhile,the covariance descriptor was used to fuse the features mentioned above to reduce the feature redundancy.The multiclass LogitBoost classifier was used for image segmentation to improve the accuracy of segmentation.Experiments on the public CamVid dataset were preformed to test and evaluate the proposed method,and the results showed that this method was effective.关键词
场景分割/运动特征/协方差描述子/LogitBoostKey words
traffic scene segmentation/ motion feature/ covariance descriptor/ LogitBoost分类
信息技术与安全科学引用本文复制引用
谭论正,夏利民..基于协方差描述子和LogitBoost的交通场景图像分割[J].湖南大学学报（自然科学版）,2013,40(8):58-63,6.基金项目
国家863计划项目(2009AA11Z205) （2009AA11Z205）
国家自然科学基金资助项目(50808025) （50808025）
国家教育部博士点基金资助项目(20090162110057) （20090162110057）
