Kinship verification from facial images under uncontrolled conditions

Authors:
Xiuzhuang Zhou;Junlin Hu;Jiwen Lu;Yuanyuan Shang;Yong Guan
Affiliations:
College of Information Engineering, Capital Normal University, Beijing, China;College of Information Science and Technology, Beijing Normal University, Beijing, China;School of Electrical and Electronics Engineering, Nanyang Technological University, Singapore, Singapore;College of Information Engineering, Capital Normal University, Beijing, China;College of Information Engineering, Capital Normal University, Beijing, China
Venue:
MM '11 Proceedings of the 19th ACM international conference on Multimedia
Year:
2011

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Abstract

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.