IEEE Trans Image Process. 2013 Dec;22(12):4798-808. doi: 10.1109/TIP.2013.2277920. Epub 2013 Aug 15.
In this paper, we present a syntactic string matching approach to solve the frontal face recognition problem. String matching is a powerful partial matching technique, but is not suitable for frontal face recognition due to its requirement of globally sequential representation and the complex nature of human faces, containing discontinuous and non-sequential features. Here, we build a compact syntactic Stringface representation, which is an ensemble of strings. A novel ensemble string matching approach that can perform non-sequential string matching between two Stringfaces is proposed. It is invariant to the sequential order of strings and the direction of each string. The embedded partial matching mechanism enables our method to automatically use every piece of non-occluded region, regardless of shape, in the recognition process. The encouraging results demonstrate the feasibility and effectiveness of using syntactic methods for face recognition from a single exemplar image per person, breaking the barrier that prevents string matching techniques from being used for addressing complex image recognition problems. The proposed method not only achieved significantly better performance in recognizing partially occluded faces, but also showed its ability to perform direct matching between sketch faces and photo faces.
在本文中，我们提出了一种句法字符串匹配方法来解决正面人脸识别问题。字符串匹配是一种强大的部分匹配技术，但由于其需要全局顺序表示以及人脸的复杂性，包含不连续和非顺序特征，因此不适合正面人脸识别。在这里，我们构建了一个紧凑的句法 Stringface 表示，它是字符串的集合。提出了一种新颖的集成字符串匹配方法，可以在两个 Stringfaces 之间执行非顺序字符串匹配。它对字符串的顺序和每个字符串的方向是不变的。嵌入的部分匹配机制使我们的方法能够在识别过程中自动使用每个未遮挡区域，而不管形状如何。令人鼓舞的结果表明，使用句法方法从每个人的单个示例图像进行人脸识别是可行和有效的，打破了阻止字符串匹配技术用于解决复杂图像识别问题的障碍。所提出的方法不仅在识别部分遮挡的面部方面取得了显著更好的性能，而且还展示了其在草图面部和照片面部之间进行直接匹配的能力。
