高精度PSO与FLS相结合的人脸地标定位方法

S. Khanmohammadi, S. M. Bakhshmand, Hadi Seyedarabi
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引用次数: 1

摘要

在平移、旋转和闪电光照变化的情况下,自动找到面部突出点的精确位置是人脸图像处理中的一个重要课题。本文提出了一种在人脸等刚性物体上寻找地标点的多阶段算法。Gabor过滤器射流使EBGM,非常有效,但计算昂贵。该方法以粒子群算法(PSO)为代价函数,以模型射流与提取射流的相似性为代价函数,对Gabor滤波射流的地标点搜索进行优化。定位第一个地标后,估计下一个地标的位置,然后通过局部搜索标准(FLS)进行优化,直到定位到所有需要的5个地标。模型喷射用于计算像素,并且可以从相同身份的地标点手动提取,以获得更高的鲁棒性和准确性。通过与穷举搜索方法的比较,验证了该方法的准确性和较低的计算成本。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
High precision PSO and FLS integrated method for facial landmark localization
Automatic finding exact location of facial salient points under translation, rotation and changing lightning illumination is a considerable task in face image processing. This paper presents a multistage procedure for finding landmark points on a rigid object like human face. Gabor filter jets make EBGM, very effective but computationally expensive. In proposed method, searching landmark points using Gabor filter jets is optimized by using particle swarm optimization (PSO) and similarity between model jet and extracted jet as cost function. After locating first landmark, the location of next landmark is estimated and then is refined by local search criteria (FLS) until localizing of all desired 5 landmarks. Model jets are used for accounting pixels and can be extracted manually from landmark points of same identity for more robustness and accuracy. Results based on the proposed approach are included to prove the accuracy and low computational cost of proposed method comparing the exhaustive search.
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