CAJ | 학술논문

由于发型、头部姿势、服装、遮挡等现象的多样性，人脸图像分割一直是一个具有挑战性的课题。为了提高复杂背景图像的人脸分割正确性，提出了一种基于多特征融合条件随机场（CRFs）的方法。该模型建立在图模型上，图中的每一个节点对应一个超像素，每一条边缘则连接一对相邻的超像素。使用颜色和纹理特征定义节点的能量函数（一元能量函数），使用位置信息和相邻超像素之间的差异定义边缘的能量函数（二元能量函数）。分割是通过条件随机场融合节点能量函数和边缘能量函数推理而得。考察了该模型在2个无约束人脸数据库上的分割性能，实验结果表明该方法可以有效地从复杂人脸图像中分割出面部皮肤、头发和背景区域。
유우발형、두부자세、복장、차당등현상적다양성，인검도상분할일직시일개구유도전성적과제。위료제고복잡배경도상적인검분할정학성，제출료일충기우다특정융합조건수궤장（CRFs）적방법。해모형건립재도모형상，도중적매일개절점대응일개초상소，매일조변연칙련접일대상린적초상소。사용안색화문리특정정의절점적능량함수（일원능량함수），사용위치신식화상린초상소지간적차이정의변연적능량함수（이원능량함수）。분할시통과조건수궤장융합절점능량함수화변연능량함수추리이득。고찰료해모형재2개무약속인검수거고상적분할성능，실험결과표명해방법가이유효지종복잡인검도상중분할출면부피부、두발화배경구역。
Face segmentation is quite challenging due to the diversity of hair styles ,head poses ,clothing ,occlusions , and other phenomena .To improve the accuracy of face segmentation from the images with complex scenes ,we present a method based on Conditional Random Fields (CRFs) in this paper .The CRFs model is defined on a graph ,in which each node corresponds to a superpixel and each edge connects a pair of neighboring superpixels .The features of color and texture are used to define the node(unary) energy function ,and the position distance and differences of features between adjacent superpixels are used to define the edge (binary) energy function .Segmentation is performed by inferring the CRFs model built by fusing node energy function and edge energy function .We evaluate the performance of the proposed method on two unconstrained face databases . Experimental results demonstrate that the proposed method can efficiently partition face .