By Frank Lin, Clinton Fookes, Vinod Chandran, Sridha Sridharan (auth.), Seong-Whan Lee, Stan Z. Li (eds.)

Many functions in government,airport, advertisement, protection and legislations enfor- mentareashaveabasicneedforautomaticauthenticationofhumansbothlocally orremotelyonaroutinebasis.Thedemandforautomaticauthenticationsystems utilizing biometrics, together with face, ?ngerprint, gait, and iris, has been expanding in lots of features of lifestyles. the aim of the 2007 overseas convention on Biometrics (ICB 2007) was once to supply a platform for researchers, engineers, s- tem architects and architects to file contemporary advances and alternate principles within the region of biometrics and comparable applied sciences. ICB 2007 acquired loads of fine quality study papers. In all 303 papers have been submitted from 29 nations world wide. of those 34 papers have been authorized for oral presentation and ninety one papers have been authorized for poster presentation. this system consisted of 7 oral periods, 3 poster classes, educational classes, and 4 keynote speeches on quite a few subject matters on biometrics. we want to thank the entire authors who submitted their manuscripts to the convention, and all of the contributors of this system Committee and reviewers who spent worthwhile time offering reviews on each one paper. we want to thank the convention administrator and secretariat for making the convention winning. We additionally desire to recognize the IEEE, IAPR, Korea details technology Society, Korea collage, Korea college BK21 software program learn department, KoreaScience and EngineeringFoundation,KoreaUniversity Institute of computing device, info and communique, Korea Biometrics organization, Lumidigm Inc., Ministry of data and conversation Republic of Korea, and Springer for sponsoring and assisting this convention. August 2007 Seong-Whan Lee Stan Z. Li association ICB 2007 used to be geared up by way of heart for Arti?cial imaginative and prescient learn, Korea University.

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Additional info for Advances in Biometrics: International Conference, ICB 2007, Seoul, Korea, August 27-29, 2007. Proceedings

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3 shows some example images of DoP. 1 Postprocessing Step Face Certainty Map For minimizing FAR(False Acceptance Rate) and FRR(False Rejection Rate), existing face detection algorithms concentrate on learning optimal model parameters and devising optimal detection algorithm. However, since the model parameters are determined by the face and non-face images in the training set, it is not guaranteed that the algorithms work well for novel images. In addition, there are infinite number of non-face patterns in real-world, accordingly it is almost impossible to train every non-face patterns in natural scene.

W. Z. ): ICB 2007, LNCS 4642, pp. 29–38, 2007. c Springer-Verlag Berlin Heidelberg 2007 30 B. Jun and D. Kim Fig. 1. The overall procedure of the proposed algorithm determine the size, location, and rotation of the selected face. These methods usually show good performance, but have difficulties in learning every non-face patterns in natural scene. In addition, these methods are somewhat slow due to much computation steps. In this paper, we present a novel face detection algorithm. For preprocessing step, we revise the modified census transform to compensate the sensitivity to the change of pixel values.

2 Weak Classifiers It is common to define the weak learners fm (x) to be the optimal threshold classification function [12], which is often called a stump. However, it is indicated in Section 2 that the value of MB-LBP features is non-metric. Hence it is impossible to use thresholdbased function as weak learner. Here we describe how the weak classifiers are designed. For each MB-LBP feature, we adopt multi-branch tree as weak classifiers. The multi-branch tree totally has 256 branches, and each branch corresponds to a certain discrete value of MB-LBP features.

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