Proceedings ArticleDOI
Biometric association using transfer subspace learning
Rupali Sandip Kute,Vibha Vyas +1 more
- pp 1384-1387
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TLDR
Two biometrics, face and fingerprint are considered and associated with each other using transfer subspace learning and the proposed framework will be very useful in the forensic applications.Abstract:
Different biometrics studies related to face, fingerprint, hand geometry, palmprint, and iris has been taken place in recent past. In this paper two biometrics, face and fingerprint are considered and associated with each other using transfer subspace learning. Transfer subspace learning can share common subspace even if domains are different by minimizing the distance between their probability distribution. Locality preserving projections is used as objective function to discriminate between source domains. This works linearly and preserves the local geometry of the structure by obtaining the subspace spanned by smallest eigenvectors of local covariance matrix. Proposed framework will be very useful in the forensic applications. Though the accuracy of this system is not very high it will help to separate the most probable suspects.read more
Citations
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Journal ArticleDOI
Component-based face recognition under transfer learning for forensic applications
TL;DR: A novel approach for component-based face recognition and association under transfer learning is proposed and it is demonstrated that the knowledge gained from complete face images is transferred to classify components of the face.
Journal ArticleDOI
Association of Face and Facial Components Based on CNN and Transfer Subspace Learning for Forensics Applications
TL;DR: For the transfer, the proposed Fisher linear discriminant analysis and locality preserving projection, a convolutional neural network-based algorithm gives 91% and 90% accuracy, respectively, which outperforms the Histogram of Gradient and Gabor methods for predicting an association.
Journal ArticleDOI
Cross domain association using transfer subspace learning
TL;DR: A cross domain association between face and fingerprint that finds utility in forensic applications is proposed and is proposed using Fisher Linear Discriminant Analysis subspace learning algorithm.
References
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Proceedings Article
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Proceedings ArticleDOI
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Si Si,Dacheng Tao,Bo Geng +2 more
TL;DR: This paper presents a family of subspace learning algorithms based on a new form of regularization, which transfers the knowledge gained in training samples to testing samples, and minimizes the Bregman divergence between the distribution of training samples and that of testing samples in the selected subspace.
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Understanding Kin Relationships in a Photo
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