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[Graph Recognize] Face_tracker DL : 0: The proposed face tracker is based on a frontal face detector that can be applied in real-time to every frame, and it is so fast that it provides the illusion of tracking.-The proposed face tracker is based on a fron tal face detector that can be applied in real-ti me to every frame. and it is so fast that it provides the illusion of tracking.
Date : 2008-10-13 Size : 5.21kb User : henry
[Graph Recognize] Intelligent_Screen_Saver DL : 0: It is a utility to control screen saver using human face detection. Human face detection is performed using OpenCV Haar-Cascade method. The software is primarily a daemon that resides in your system tray and keeps observing the input from a webcam to analyze if the user is no longer in view. Currently two angles are supported namely frontal pose and profile pose.
Date : 2008-10-13 Size : 96.49kb User : 萧董
[Graph Recognize] Face_tracker DL : 0: The proposed face tracker is based on a frontal face detector that can be applied in real-time to every frame, and it is so fast that it provides the illusion of tracking.-The proposed face tracker is based on a fron tal face detector that can be applied in real-ti me to every frame. and it is so fast that it provides the illusion of tracking.
Date : 2025-12-25 Size : 5kb User : henry
[Graph Recognize] Intelligent_Screen_Saver DL : 0: It is a utility to control screen saver using human face detection. Human face detection is performed using OpenCV Haar-Cascade method. The software is primarily a daemon that resides in your system tray and keeps observing the input from a webcam to analyze if the user is no longer in view. Currently two angles are supported namely frontal pose and profile pose.
Date : 2025-12-25 Size : 96kb User : 萧董
[Graph Recognize] A-FaceDetection-Based-on-Frontal-InverseAdaboostAl DL : 0: 人脸的检测和跟踪对于自由立体显示非常重要。本文采用连续Adaboost算法学习出一种瀑布型的人脸检测器，同时针对adaboost算法误检率比较高的弊病，提出了一种正反Adaboost检测的思想，最后通过利用已有积分图以及最小值滤波，完成了对人眼的识别操作。实验结果表明，算法对现有adaboost算法精度上的改进令人满意，基本能满足自由立体显示的需要。 -Accuratelylocatingandtrackingthepositionoftheusefsfaceisimop rtantforautostereoscopicdisplay．A casacdefacedetectorlearntbyusingraelAdabo stalgorithm ispresented，andforthepurop seofreducingthefalse alarm，anovelprocedurecalledFrontal—InverseAdabo stisproposed，thenaprocesstogainaccurateeyes’loac— tionsisexecutedwithminimum filterna dintegralimage．A setofexperimentsarepresented．theresultsindiacte thattheprecisionimprovingtonormalAdabo stalgorithm issatisfying．Itacnbeseenthattheproposedmethodis veryefifcientandhaslotsofsigniifcantvaluestoautostereoscopicdisplay．
Date : 2025-12-25 Size : 186kb User : coco_220
[Graph Recognize] imm_face_db DL : 0: imm_face_db_zip是基于IMM的人脸数据库，里面的包含不同姿态的人脸：有正面人脸、左右分别倾斜30度的人脸及其相应的asf信息，对AAM的建模有着重要的作用。-imm_face_db_zip is based on the IMM Face Database, which contains the human face of different poses: a frontal face, tilted about 30 degrees, respectively, and their corresponding asf face information, AAM has an important role in the modeling.
Date : 2025-12-25 Size : 26mb User : 郭涵
[Graph Recognize] FACE-RECOGNITION DL : 0: 此文的目的有三个：第一，当地连续均值量化变换特征是提出照明和传感器敏感操作在目标识别上。其次，注册稀疏Winnows网络分割，提出了加快原分类。最后，特点和分类相结合对于正面人脸检测任务。检测结果列为MIT + CMU系统和BioID数据库。关于这人脸检测器，接收器操作特征曲线BioID数据库产生最好的结果公布。对于结果麻省理工学院的中央结算系统+数据库相当于国家的最先进的脸探测器。一个人脸检测算法的MATLAB版本可以从http://www.mathworks.com/matlabcentral/fileexchange/ loadFile.do？的ObjectID = 13701＆的objectType =FILE下载。 -The purpose of this paper is threefold: firstly, the local Successive Mean Quantization Transform features are proposed for illumination and sensor insensitive operation in object recognition. Secondly, a split up Sparse Network of Winnows is presented to speed up the original classifier. Finally, the features and classifier are combined for the task of frontal face detection. Detection results are presented for the MIT+CMU and the BioID databases. With regard to this face detector, the Receiver Operation Characteristics curve for the BioID database yields the best published result. The result for the CMU+MIT database is comparable to state-of-the-art face detectors. A Matlab version of the face detection algorithm can be downloaded from http://www.mathworks.com/matlabcentral/fileexchange/ loadFile.do?objectId=13701&objectType=FILE.
Date : 2025-12-25 Size : 1.33mb User : 霞