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脸部识别技术及运用 [2]

论文作者:www.51lunwen.org论文属性:职称论文 Scholarship Papers登出时间:2015-03-27编辑:Cinderella点击率:9032

论文字数:2940论文编号:org201503261537485917语种:英语 English地区:英国价格:免费论文

关键词:Face detectionface tracking人脸识别技术

摘要:本文对人脸识别技术的种类、操作原理和运用进行了详细介绍。尤其是脸部识别、脸部追踪和面部表情识别等问题上的运用成果展示。

e skin color, face shape, or facial features like eyes, nose, etc... Feature based methods are preferred for real time systems where the multi-resolution window scanning used by image based methods are not applicable. Human skin color is an effective feature used to detect faces, although different people have different skin color, several studies have shown that the basic difference based on their intensity rather than their chrominance. For detecting face there are various algorithms including skin color based algorithms. Color is known to be a useful cue to extract skin regions, and it is only available in color images. Using skin-color as a feature for tracking a face has several advantages. Color processing is much faster than processing other facial features. Under certain lighting conditions, color is orientation invariant. This property makes motion estimation much easier because only a translation model is needed for motion estimation. Color is not a physical phenomenon; it is a perceptual phenomenon that is related to the spectral characteristics of electromagnetic radiation in the visible wavelengths striking the retina. Tracking human faces using color as a feature has several problems like the color representation of a face obtained by a camera is influenced by many factors (ambient light, object movement, etc.), different cameras produce significantly different color values even for the same person under the same lighting conditions and skin color differs from person to person. In order to use color as a feature for face tracking, we have to solve these problems. It is also robust towards changes in orientation and scaling and can tolerate occlusion well. A disadvantage of the color cue is its sensitivity to illumination color changes and, especially in the case of RGB, sensitivity to illumination intensity. One way to increase tolerance toward intensity changes in images is to transform the RGB image into a color space whose intensity and chromaticity are separate and use only chromaticity part for detection. Eyes are the most important features of human face. There are many applications of the robust eye states extraction. For example, the eye states provide important information for recognizing facial expression and human-computer interface systems. An automatic and robust technique to extract the eye states from input images is very important in this field. In this paper, eyes are detected by using Hough transform. We are applying Circular Hough transform in order to detect the circular object in the image. In human face eyeball, pupils are in circular shape; hence by using circular Hough transform eye can be detected.

 

MODEL FOR SKIN COLOR DETECTION

 

Detection of skin color in color images is a very popular and useful technique for face detection. The common approach to skin detection is using the skin color as feature, whereby estimating areas with skin color is often the first vital step of such strategy. Hence, skin color classification has become an important task. Classifying the pixels of an input image in two groups; skin and non-skin pixels. An important requirement for automatic skin detection systems is a tradeoff between correct classification rate and response t论文英语论文网提供整理,提供论文代写英语论文代写代写论文代写英语论文代写留学生论文代写英文论文留学生论文代写相关核心关键词搜索。

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