Description: 视频搜索中人脸识别关键技术的研究与实现。本文对人脸检测与识别技术进行了研究，实现了一个用于视频搜
索的自动人脸识别系统。该系统对输入的视频帧进行人脸检测和定
位，经过图像预处理之后，进行重要特征点Gabor一Fisher的特征提取
和分类识别。-Video search, face recognition and implementation of key technologies. In this paper, face detection and recognition technology has been studied to realize an automatic face recognition for video search system. The system of input video frames for face detection and location, after image pre-processing carried out following important features of a Fisher-point Gabor feature extraction and classification and recognition. Platform: |
Size: 4003840 |
Author:王帅 |
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Description: 人脸识别关键技术的研究与实现,对人脸检测与识别技术进行了研究，实现了一个用于视频搜索的自动人脸识别系统,该系统对输入的视频帧进行人脸检测和定位.-The key technology of face recognition and realization of human face detection and recognition technology has been studied to achieve an automatic face recognition for video search system, the input video frames for face detection and location. Platform: |
Size: 468992 |
Author:抛弃 |
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Description: This thesis proposes a novel algorithm for integrated face detection and face tracking
based on the synthesis of an adaptive particle filtering algorithm and an AdaBoost face detection
algorithm. A novel Adaptive Particle Filter (APF), based on a new sampling technique, is
proposed to obtain accurate estimation of the proposal distribution and the posterior distribution
for accurate tracking in video sequences. The proposed scheme, termed a Boosted Adaptive
Particle Filter (BAPF), combines the APF with the AdaBoost algorithm. The AdaBoost
algorithm is used to detect faces in input image frames, while the APF algorithm is designed to
track faces in video sequences. The proposed BAPF algorithm is employed for face detection,
face verification, and face tracking in video sequences. Experimental results confirm that the
proposed BAPF algorithm provides a means for robust face detection and accurate face tracking
under various tracking scenarios. Platform: |
Size: 1057792 |
Author:Trabelsi |
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Description: 使用vision.cascadeobjectdetector检测视频帧中的人眼的位置。检测器使用提琴琼斯检测算法和检测训练分类模型。人脸跟踪使用KLT算法.能够减少人头倾斜造成的影响,只有第一次检测人眼，以后都是检测特征点，运算速度快。-Use vision.cascadeobjectdetector detects video frames eye position. The detector uses a detection algorithm Tiqinqiongsi classification model training and testing. Face tracking using KLT algorithm can reduce the impact caused by the tilt of the head, only the first detection of the human eye, after all detected feature points, computing speed. Platform: |
Size: 1024 |
Author:lidong |
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Search - video frames detection face