计算机工程与设计
計算機工程與設計
계산궤공정여설계
COMPUTER ENGINEERING AND DESIGN
2009年
24期
5790-5792
,共3页
人体目标检测%Gabor变换%Adaboost算法%特征提取%特征选择
人體目標檢測%Gabor變換%Adaboost算法%特徵提取%特徵選擇
인체목표검측%Gabor변환%Adaboost산법%특정제취%특정선택
human detection%Gabor transform%Adaboost algorithm%feature extraction%feature selection
针对在图像中检测人体目标,提出一种基于Gabor变换和Adaboost算法的检测方法.首先利用二维Gabor小波变换进行特征提取,然后利用Adaboost算法对Gabor特征进行选取并训练强分类器.为了提高检测精度,提出采用单一正样本集合与多个负样本集合分别进行训练,形成多个强分类器级联的层级检测分类器.实验结果表明了该方法的有效性,同时显示该方法须与其它辅助手段相结合,才能提高检测的实时性.
針對在圖像中檢測人體目標,提齣一種基于Gabor變換和Adaboost算法的檢測方法.首先利用二維Gabor小波變換進行特徵提取,然後利用Adaboost算法對Gabor特徵進行選取併訓練彊分類器.為瞭提高檢測精度,提齣採用單一正樣本集閤與多箇負樣本集閤分彆進行訓練,形成多箇彊分類器級聯的層級檢測分類器.實驗結果錶明瞭該方法的有效性,同時顯示該方法鬚與其它輔助手段相結閤,纔能提高檢測的實時性.
침대재도상중검측인체목표,제출일충기우Gabor변환화Adaboost산법적검측방법.수선이용이유Gabor소파변환진행특정제취,연후이용Adaboost산법대Gabor특정진행선취병훈련강분류기.위료제고검측정도,제출채용단일정양본집합여다개부양본집합분별진행훈련,형성다개강분류기급련적층급검측분류기.실험결과표명료해방법적유효성,동시현시해방법수여기타보조수단상결합,재능제고검측적실시성.
A detection method based on Gabor transform and Adaboost algorithm is proposed to detect human objects in images. The basic idea of this algorithm is to perform feature selection by using the 2D Gabor transform and then obtain strong classifiers by using the Adaboost algorithm. To increase the detection rate, a single positive sample set is trained with multiple negative sample sets to generate a cascade classifier composed of several strong classifiers. Experimental results prove the validity of this method, and show that this method must be combined with other supplementary means to improve the real time performance of detection.
