Kinship verification from facial images under uncontrolled conditions
Xiuzhuang Zhou, Junlin Hu, Jiwen Lu, Yuanyuan Shang, Yong Guan · 2011
In this paper, we present an automatic kinship verification system based on facial image analysis under uncontrolled conditions. While a large number of studies on human face analysis have been performed in the literature, there are a few attempts on automatic face analysis for kinship verification, possibly due to lacking of such publicly available databases and great challenges of this problem. To this end, we collect a kinship face database by searching 400+ pairs of public figures and celebrities from the internet, and automatically detect them with the Viola-Jones face detector. Then, we propose a new spatial pyramid learning-based (SPLE) feature descriptor for face representation and apply support vector machine (SVM) for kinship verification. The proposed system has the following three characteristics: 1) no manual human annotation of face landmarks is required and the kinship information is automatically obtained from the original pair of images; 2) both local appearance information and global spatial information have been effectively utilized in the proposed SPLE feature descriptor, and better performance can be obtained than state-of-the-art feature descriptors in our application; 3) the performance of our proposed system is comparable to that of human observers.