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Published in:
2011 | OriginalPaper | Chapter
Family Facial Patch Resemblance Extraction
Authors : M. Ghahramani, W. Y. Yau, E. K. Teoh
Published in: Computer Vision – ACCV 2010
Publisher: Springer Berlin Heidelberg
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Family members have close facial resemblances to one another; especially for certain specific parts of the face but the resemblance part differ from family to family. However, we have no problem in identifying such facial resemblances to guess the family relationships. This paper attempts to develop such human capability in computers through measurements of the resemblance of each facial patch to classify family members. To achieve this goal, family datasets are collected. A modified Golden Ratio Mask is implemented to guide the facial patches. Features of each facial patch are selected, analyzed by an individual classifier and the importance of each patch is extracted to find the set of most informative patches. To evaluate the performance, various scenarios where different members of the family are absent from training but present in testing are tested to classify the family members. Results obtained show that we can achieve up to 98% average accuracy on the collected dataset.