Description: 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. Platform: |
Size: 92401 |
Author:陈实 |
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Description: 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. Platform: |
Size: 98802 |
Author:萧董 |
Hits:
Description: 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. Platform: |
Size: 92160 |
Author:陈实 |
Hits:
Description: 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. Platform: |
Size: 98304 |
Author:萧董 |
Hits:
Description: 研究描述人脸特征的有效方法, 讨论身份证照片的特征提取和检索采用自适应肤色检测技术改进通用的肤色检测算法, 进行脸部区域的划分提出系数投影法对面部五官区域进行分割, 在各区域中提取面部几何特征引人描述脸颊和下额轮廓的曲线参数作为脸形特征, 得到对人脸特征更准确的描述将面部几何特征矢量匹配、脸形曲线参数匹配和脸部图像相关匹配相结合, 实现人像照片的准确检索实验表明该方法性能优良。-Describe the facial features of an effective way to discuss the ID card photo feature extraction and retrieval using adaptive skin color detection techniques improve the general detection algorithm for facial areas by the proposed coefficient of projection of the facial features to segment the region, in the Extraction of geometric features of the region face cheeks and under the places described in the introduction of profile parameters of the curve as facial features, facial features and get the more accurate description of the feature vector matching facial geometry, face curve parameter matching and matching facial images related to the combination of to achieve an accurate portrait photo retrieval experiments show that the method excellent. Platform: |
Size: 699392 |
Author:郭事业 |
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Description: Face detection algorithms are widely used in computer vision as they provide fast and reliable results depending on the application
domain. A multi view approach is here presented to detect frontal and profile pose of people face using Histogram of Oriented Gradients, i.e. HOG, features. A K-mean clustering technique is used in a cascade of HOG feature classifiers to detect faces. The evaluation of the algorithm shows similar performance in terms of detection rate as state of the art algorithms. Moreover, unlike state of the art algorithms,our system can be quickly trained before detection is possible. Performance is considerably increased in terms of lower computational cost and lower false detection rate when combined with motion constraint given by moving objects in video sequences. The detected HOG features are integrated within a tracking framework and allow reliable face tracking results in several tested surveillance video sequences. Platform: |
Size: 293888 |
Author:linuszhao |
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Description: 本文运用深度神经网络的方法克服姿态变量和图像分辨率的影响,提出了一种多姿态的人脸超分辨识别算法并在实验数据集上获得了良好的性能表现。另外本文利用深度信念网络探索正面人脸图像和侧面人脸图像的映射,方法放松了深度信念网络的输入也输出之间绝对相等,而只是保证其高层含义上的相等。实验表明了使用深度信念网络可以学习到侧面人脸图像到正面人脸图像的一个全局映射,但是丢失了个体细节差异。本文还提出了基于深度网络保持姿态邻域进行姿态分类的方法,在学习过程中,我们保证了同一个姿态下的人脸图像应该与同一姿态下的多张图像互为邻居。实验证明了,我们的方法在用于姿态分类具有非常良好的性能,但是也发现学习过程中,那些与区别个体的信息逐渐丢失了,这也导致了直接运用非线性近邻元分析的特征的人脸识别的性能不佳。-In this paper, the neural network approach to overcome the depth of variables that affect the attitude and image resolution , proposed a multi-pose face recognition algorithms and super-resolution experimental data set obtained in a good performance. Also this paper to explore the depth of belief network mapping frontal face image and profile face images , the method of absolute equality between the input relax depth of belief networks is also output , but only to ensure equal meaning on its top . Experimental results show that the use of deep belief networks can learn to face image to the side of the front face of a global image map , but lost the details of individual differences . This paper also proposes to maintain posture neighborhood depth network-based gesture classification methods in the learning process , we ensure that the face image under the same gesture with multiple images should be under the same attitude are neighbors . Experiment proves that our method for gesture cl Platform: |
Size: 9719808 |
Author:cen |
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Search - face frontal profile