Nonlinear Metric Learning with Deep Independent Subspace Analysis Network for Face Verification
نویسندگان
چکیده
منابع مشابه
Cosine Similarity Metric Learning for Face Verification
Face veri cation is the task of deciding by analyzing face images, whether a person is who he/she claims to be. This is very challenging due to image variations in lighting, pose, facial expression, and age. The task boils down to computing the distance between two face vectors. As such, appropriate distance metrics are essential for face veri cation accuracy. In this paper we propose a new met...
متن کاملDiscriminant Metric Learning Approach for Face Verification
In this study, we propose a distance metric learning approach called discriminant metric learning (DML) for face verification, which addresses a binary-class problem for classifying whether or not two input images are of the same subject. The critical issue for solving this problem is determining the method to be used for measuring the distance between two images. Among various methods, the lar...
متن کاملPost Nonlinear Independent Subspace Analysis
In this paper a generalization of Post Nonlinear Independent Component Analysis (PNL-ICA) to Post Nonlinear Independent Subspace Analysis (PNL-ISA) is presented. In this framework sources to be identified can be multidimensional as well. For this generalization we prove a separability theorem: the ambiguities of this problem are essentially the same as for the linear Independent Subspace Analys...
متن کاملSignature Embedding: Writer Independent Offline Signature Verification with Deep Metric Learning
The handwritten signature is widely employed and accepted as a proof of a person’s identity. In our everyday life, it is often verified manually, yet only casually. As a result, the need for automatic signature verification arises. In this paper, we propose a new approach to the writer independent verification of offline signatures. Our approach, named Signature Embedding, is based on deep metr...
متن کاملDeep Nonlinear Metric Learning for Speaker Verification in the I-Vector Space
Speaker verification is the task of determining whether two utterances represent the same person. After representing the utterances in the i-vector space, the crucial problem is only how to compute the similarity of two i-vectors. Metric learning has provided a viable solution to this problem. Until now, many metric learning algorithms have been proposed, but they are usually limited to learnin...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IEICE Transactions on Information and Systems
سال: 2013
ISSN: 0916-8532,1745-1361
DOI: 10.1587/transinf.e96.d.2830