论文标题
Agrupamento de Pixel
Agrupamento de Pixels para o Reconhecimento de Faces
论文作者
论文摘要
这项研究始于这样的观察，即面部识别可能会因大量图像收缩而产生较低的影响。为了解释这一事实，我们提出了像素聚类方法。它在图像中定义了其像素非常相似的图像中的区域。我们从每个区域提取特征。我们在实验中使用了三个面部数据库。我们注意到512是高精度图像识别所需的最大功能数量。提出的方法也很健壮，即使它只使用培训集中的几个类。
This research starts with the observation that face recognition can suffer a low impact from significant image shrinkage. To explain this fact, we proposed the Pixel Clustering methodology. It defines regions in the image in which its pixels are very similar to each other. We extract features from each region. We used three face databases in the experiments. We noticed that 512 is the maximum number of features needed for high accuracy image recognition. The proposed method is also robust, even if only it uses a few classes from the training set.
