A Detection Strategy of Multi-Pose Face in Compressed Domain武汉大学学报：自然科学英文版论文
【题名】：A Detection Strategy of Multi-Pose Face in Compressed Domain武汉大学学报：自然科学英文版论文(A Detection Strategy of Multi-Pose Face in Compressed DomainWuHanDaXueXueBao：ZiRanKeXueYingWenBanLunWen) 【关键词】：多面部姿态 压缩范围 增压算法 图像识别 图像分类 【keywords】：DuoMianBuZiTai YaSuoFanWei ZengYaSuanFa TuXiangShiBie TuXiangFenLei 【作者】：CHENLei,ZHOUGuo-fu,      【来源】： 知识词典 【期刊名称】：武汉大学学报：自然科学英文版(WuHanDaXueXueBao：ZiRanKeXueYingWenBan) 【国际标准刊号】：1007-1202        【国内统一刊号】：42-1405/N 【作者单位】：[1]SchoolofComputing.NationalUniversityofSingapore,Singapore117513 [2]StateTechnologyCenterofMultimediaSoftwareEngineering.WuhanUniversity.Wuhan430072,Hubei.China([1]SchoolofComputing.NationalUniversityofSingapore,Singapore117513 [2]StateTechnologyCenterofMultimediaSoftwareEngineering.WuhanUniversity.Wuhan430072,Hubei.China) 【分类号】：TP391.41      【页码】：-845-850      【出版年】：2004.5 【下载地址】：下载pdf全文         In this paper, we present a strategy to implement multi pose face detection in compressed domain. The strategy extracts firstly feature vectors from DCT domain, and then uses a boosting algorithm to build classifiers to distinguish faces and non-faces. Moreover. to get more accurate results of the face detection, we present a kernel function and a linear combination to build incrementally the strong classifiers based on the weak classifiers. Through comparing and analyzing results of some experiments on the synthetic data and the natural data, we can get more satisfied results by the strong classifiers than by the weak classifies.
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