基于HOG描述符的素描图像人脸识别

G. G. Rajput, Prashantha, B. Geeta
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引用次数: 5

摘要

在本文中,我们提出了一种高效的草图与人脸图像匹配算法。该系统利用以定向梯度直方图(HOG)特征描述符表示的面部区域中存在的判别信息,根据艺术家绘制的查询草图从数据库中提取人脸照片。从由照片人脸组成的训练集中提取hog特征并作为知识库存储。给定一个艺术家草图,计算草图的hog值,并与知识库进行比较,应用KNN分类器检索最匹配的照片人脸。在我们的研究中,我们考虑了正面姿势与正常照明和中性表情的脸部照片。假设照片中没有遮挡。在中大学生的人脸素描和照片数据库中进行了实验。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Face Photo Recognition from Sketch Images Using HOG descriptors
In this paper, we propose an efficient algorithm for matching sketches with face-photo images. The proposed system extracts face photo from the database based on a query sketch drawn by an artist by using discriminating information present in the facial regions represented as histogram of oriented gradients (HOG) feature descriptor. From the training set consisting of photo-faces, HOGs features are extracted and stored as knowledge base. Given, an artist sketch, HOGs of the sketch are computed and are compared against the knowledge base by applying KNN classifier for retrieval of best matching photo face. In our study we have considered face photos of frontal pose with normal lighting and neutral expression. No occlusions in the photo are assumed. Experiments are conducted on CUHK student database of face sketches and photos.
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