电子器件
電子器件
전자기건
JOURNAL OF ELECTRON DEVICES
2014年
4期
626-630
,共5页
人脸检测%局部线性嵌入%深度%降维%随机森林
人臉檢測%跼部線性嵌入%深度%降維%隨機森林
인검검측%국부선성감입%심도%강유%수궤삼림
face detection%locally linear embedding( LLE)%depth%dimension reduction%random forest
针对人脸检测问题的特点,提出一种基于改进型深度LLE( Locally Linear Embedding)算法和随机森林相结合的人脸检测算法。首先,通过采集图像的深度信息,结合图像的颜色信息,构建三维图像信息数据库,再通过改进的LLE算法得到最优降维结果,按一定比例选取训练集,输入随机森林算法建立数据分类器；最后,将测试集输入到训练完成的分类器中,实现人脸图像的检测。选取Yale,JAFFE 2类数据集与传统算法进行对比实验,验证算法的优越性和可行性。实验结果表明：所提出的算法可以有效地完成人脸检测,检测率高于传统算法7%左右。
針對人臉檢測問題的特點,提齣一種基于改進型深度LLE( Locally Linear Embedding)算法和隨機森林相結閤的人臉檢測算法。首先,通過採集圖像的深度信息,結閤圖像的顏色信息,構建三維圖像信息數據庫,再通過改進的LLE算法得到最優降維結果,按一定比例選取訓練集,輸入隨機森林算法建立數據分類器；最後,將測試集輸入到訓練完成的分類器中,實現人臉圖像的檢測。選取Yale,JAFFE 2類數據集與傳統算法進行對比實驗,驗證算法的優越性和可行性。實驗結果錶明：所提齣的算法可以有效地完成人臉檢測,檢測率高于傳統算法7%左右。
침대인검검측문제적특점,제출일충기우개진형심도LLE( Locally Linear Embedding)산법화수궤삼림상결합적인검검측산법。수선,통과채집도상적심도신식,결합도상적안색신식,구건삼유도상신식수거고,재통과개진적LLE산법득도최우강유결과,안일정비례선취훈련집,수입수궤삼림산법건립수거분류기；최후,장측시집수입도훈련완성적분류기중,실현인검도상적검측。선취Yale,JAFFE 2류수거집여전통산법진행대비실험,험증산법적우월성화가행성。실험결과표명：소제출적산법가이유효지완성인검검측,검측솔고우전통산법7%좌우。
For the characteristics of face detection,a novel face detection algorithm based on modified depth Locally Linear Embedding(LLE)and Random Forest is proposed. Firstly,the depth information of images are collected by Kinect, and the three-dimensional image data base can be established by the depth information and colour information. Secondly, the dimension of data sets are reduced by modified LLE, and the optimal results of data dimension reduction can be gotten. The training sets are gotten by the proportion of data sets,and data classifier can be gotten by Random Forest. Finally,the test sets are input,and the face detection can be achieved. The two classes of data sets are selected as the experimental data,which consist of Yale and JAFFE. The experiment results show that the proposed method not only has a great effect to achieve face detection,but the detection rate is higher than the traditional algorithms about 7%.
