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Description: 本文完成了对唇动身份识别技术几个基本问题的理论研究,并对整个系统加以实现.作为本文研究的实验基础,我们建立了唇动方式身份识别数据库(HITLUDB),
该库目前包含30个说话人每人20个汉语词的音视频语料.数据库的扩充与完善工作仍在不断的进行之中.在嘴唇检测方面,
我们对自适应色度过滤模型进行改进,提高了算法的鲁棒性,完成了对嘴唇的精确定位.结合DCT变换与K-L变换的各自特点,
我们提出了特征提取算法,使用较少维数的特征完成了对嘴唇区域主要信息的刻画.由于唇动信息同时包含了生理特征与行为特征,
我们使用静念动念混合建模的方式,完成了对说话人唇动个性特点的精确描述.在HMM训练时,我们提出了特征的归一化处理方法,提高了HMM在实际应用中的性能.
最后,我们分别对身份辨认系统与身份确认系统的基本理论进行了叙述,并完成了系统的实践工作.
关 键 词：身份识别 唇动 特征提取 隐马尔可夫模型 K-L变换 -paper completed the lip movements identification technology several basic issues of theoretical study, system as a whole be achieved. As this paper, the experimental basis, We have established a dynamic manner lip identification database (HITLUDB) The library currently contains 30 words each of 20 Chinese words, sound and video corpus. and the expansion of the database is still perfect keep going on. Detection of the lips, we adaptive color filter model improvements, improve the robustness of the algorithm, completed a pair of lips the precise positioning. DCT combined with the K-L transform their own characteristics, We have proposed a feature extraction algorithm, use less dimension of the lips completed the main message of regional characterization. As the lip movements of information,
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Size: 5222806 |
Author: 李岚熙 |
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Description: 本文完成了对唇动身份识别技术几个基本问题的理论研究,并对整个系统加以实现.作为本文研究的实验基础,我们建立了唇动方式身份识别数据库(HITLUDB),
该库目前包含30个说话人每人20个汉语词的音视频语料.数据库的扩充与完善工作仍在不断的进行之中.在嘴唇检测方面,
我们对自适应色度过滤模型进行改进,提高了算法的鲁棒性,完成了对嘴唇的精确定位.结合DCT变换与K-L变换的各自特点,
我们提出了特征提取算法,使用较少维数的特征完成了对嘴唇区域主要信息的刻画.由于唇动信息同时包含了生理特征与行为特征,
我们使用静念动念混合建模的方式,完成了对说话人唇动个性特点的精确描述.在HMM训练时,我们提出了特征的归一化处理方法,提高了HMM在实际应用中的性能.
最后,我们分别对身份辨认系统与身份确认系统的基本理论进行了叙述,并完成了系统的实践工作.
关 键 词：身份识别 唇动 特征提取 隐马尔可夫模型 K-L变换 -paper completed the lip movements identification technology several basic issues of theoretical study, system as a whole be achieved. As this paper, the experimental basis, We have established a dynamic manner lip identification database (HITLUDB) The library currently contains 30 words each of 20 Chinese words, sound and video corpus. and the expansion of the database is still perfect keep going on. Detection of the lips, we adaptive color filter model improvements, improve the robustness of the algorithm, completed a pair of lips the precise positioning. DCT combined with the K-L transform their own characteristics, We have proposed a feature extraction algorithm, use less dimension of the lips completed the main message of regional characterization. As the lip movements of information,
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Size: 5222400 |
Author: QHLee |
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Description: 这是一个口形特征点粗定位程序，首先对唇部图象进行边缘检测，然后利用几何特征进行定位。-This is a lip feature points coarse positioning procedures, first of all on the lip image edge detection, and then positioning the use of geometrical features.
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Size: 2048 |
Author: 李莉 |
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Description: 人脸检测+眼睛检测（模版匹配）+瞳孔检测+嘴唇检测（cameshift）-face detection+ eye detection( template match)+pupil detection+lip detection (camshift)
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Size: 48332800 |
Author: briend |
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Description: Abstract—This paper proposes a new technique for face detection
and lip feature extraction. A real-time field-programmable
gate array (FPGA) implementation of the two proposed techniques
is also presented. Face detection is based on a naive Bayes classifier
that classifies an edge-extracted representation of an image. Using
edge representation significantly reduces the model’s size to only
5184 B, which is 2417 times smaller than a comparable statistical
modeling technique, while achieving an 86.6 correct detection
rate under various lighting conditions. Lip feature extraction uses
the contrast around the lip contour to extract the height and width
of the mouth, metrics that are useful for speech filtering. The
proposed FPGA system occupies only 15 050 logic cells, or about
six times less than a current comparable FPGA face detection
system.-Abstract—This paper proposes a new technique for face detection
and lip feature extraction. A real-time field-programmable
gate array (FPGA) implementation of the two proposed techniques
is also presented. Face detection is based on a naive Bayes classifier
that classifies an edge-extracted representation of an image. Using
edge representation significantly reduces the model’s size to only
5184 B, which is 2417 times smaller than a comparable statistical
modeling technique, while achieving an 86.6 correct detection
rate under various lighting conditions. Lip feature extraction uses
the contrast around the lip contour to extract the height and width
of the mouth, metrics that are useful for speech filtering. The
proposed FPGA system occupies only 15 050 logic cells, or about
six times less than a current comparable FPGA face detection
system.
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Size: 28409856 |
Author: ramanaidu |
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Description: code for lip detection
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Size: 13312 |
Author: reza Banimahd |
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Description: 实现一种结合颜色空间、变换及变形模板的自动唇部定位及唇轮廓提取、跟踪方法首先在空间建立肤色模型进行人脸检测、定位, 并由人脸几何特征进行唇部粗定位然后结合唇色模型进行变换使肤、唇色差别明显化, 提出根据亮度信息对变换结果预处理后用法进行图像分割, 经唇色模型进一步验证后实现唇部精定位再使用变形模板来进行嘴唇轮廓特征提取, 为增强内轮廓定位的鲁棒性, 对经亮度预处理和唇色模型验证得到的口腔区域边缘图进行曲线拟合来实现内轮廓定位最后, 将唇读图像序列中上一帧的唇部定位结果拓展后作为当前帧的预测区域再进行处理来实现唇动跟踪。-To achieve a combination of color space, transform and deformable template automatic lip localization and lip contour extraction, tracking the establishment of the first color model in the space of face detection, location, geometric features of the face by the rough location and then combined with lip lip transformation so that the skin color model, lip color difference visible, presented the results according to the luminance information to transform the image after pretreatment use of segmentation, and further validated by the lip model to achieve precise positioning and then use the deformation of the lip template for lip contour extraction , to enhance the robustness of location within the outline, by the brightness of the pretreatment and the lip model validation by oral Quyu edge map to fit curve to achieve the final positioning within the contour, the lip-reading image sequence in the last frame of the lips After positioning results extend the forecast area as the current frame
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Size: 970752 |
Author: 郭事业 |
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Description: 这是一篇详细介绍人脸检测与语音驱动口型的文章，其中使使用了高斯混合模型采取了无监督聚类的方法，希望对你有用。
-This is a detailed introducer face detection and voice-driven lip article, which makes use of a Gaussian mixture model to take unsupervised clustering methods, hope useful for you.
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Size: 251904 |
Author: qijgd |
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Description: LBP已经成功应用于人脸检测，唇语识别，表情检测，动态纹理等等领域。其算法复杂度低，消耗内存小，原理简单.-LBP has been successfully applied to face detection, lip recognition, face detection, dynamic texture and so on. Its low algorithm complexity and memory consumption is small, simple principle.
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Size: 4096 |
Author: 王筝 |
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Description: 人脸作为图像与视频中最重要的视觉对象之一，是智能人机接口等许多应用的处理目标对象。近年来，人脸检测技术在模式识别、计算机视觉、人机交互等诸多领域引起了普遍重视。之所以人脸检测技术在当今计算机视觉等领域的研究中占有重要的地位并成为研究焦点，主要在于以下两个方面：一方面将人脸作为基本是绝对想来考虑，子等检测与定位人脸是实现人脸识别、人脸跟踪、表情识别、人联合成与人脸编码、唇读等技术的必要前提(Face is one of the most important visual objects in image and video, and it is the target of many applications such as intelligent human computer interface. In recent years, face detection technology has attracted widespread attention in many fields, such as pattern recognition, computer vision, human-computer interaction and so on. The research of face detection technology in the field of computer vision and other plays an important role and become the focus of research, mainly in the following two aspects: on the one hand will face as basic is absolutely want to consider, such as face detection and location is a prerequisite for face recognition, face tracking, face recognition, and joint face encoding, lip reading technology; on the other hand)
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Size: 651264 |
Author: alicemlp
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