CAJ | 학술논문

针对传统ASM方法进行人脸面部特征定位的一些缺点,提出了几点改进算法。传统的ASM方法难以在每一个特征点上都取得较好的匹配结果,并且由于背景图像的不确定性,训练得到的模型依赖于训练样本的背景。针对以上问题,首先针对边缘特征点,提出复杂背景下的局部纹理模型;其次,针对轮廓的角点,使用二维模型和二维的特征点匹配算法;最后,在局部灰度模型中加入了边缘约束,使边缘信息较强的点有更大的可能成为最佳候选点。实验结果表明,改进算法与仿真算法比较,准确性和鲁棒性均有明显提高。
침대전통ASM방법진행인검면부특정정위적일사결점,제출료궤점개진산법。전통적ASM방법난이재매일개특정점상도취득교호적필배결과,병차유우배경도상적불학정성,훈련득도적모형의뢰우훈련양본적배경。침대이상문제,수선침대변연특정점,제출복잡배경하적국부문리모형;기차,침대륜곽적각점,사용이유모형화이유적특정점필배산법;최후,재국부회도모형중가입료변연약속,사변연신식교강적점유경대적가능성위최가후선점。실험결과표명,개진산법여방진산법비교,준학성화로봉성균유명현제고。
This paper makes several improvements of traditional active shape model for face orientation.It is hard for the conventional ASM to match accurately on each landmark;what＇s more,the trained model depends heavily on the clutter background.In view of the drawbacks mentioned above,firstly,we propose the local texture model in clutter background;secondly,we design the 2-D model for corner points;and lastly,we add fringe restrain in the model of partial grey level,so that the points with strong fringe information could have more possibility to become the perfect candidate points.Experiment results show that the improved algorithm is superior to those available in accuracy and robustness.