AIMC Topic: Biometric Identification

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Learning Sparse and Identity-Preserved Hidden Attributes for Person Re-Identification.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Person re-identification (Re-ID) aims at matching person images captured in non-overlapping camera views. To represent person appearance, low-level visual features are sensitive to environmental changes, while high-level semantic attributes, such as ...

Biometric identification of listener identity from frequency following responses to speech.

Journal of neural engineering
OBJECTIVE: We investigate the biometric specificity of the frequency following response (FFR), an EEG marker of early auditory processing that reflects phase-locked activity from neural ensembles in the auditory cortex and subcortex (Chandrasekaran a...

Leader-Based Multi-Scale Attention Deep Architecture for Person Re-Identification.

IEEE transactions on pattern analysis and machine intelligence
Person re-identification (re-id) aims to match people across non-overlapping camera views in a public space. This is a challenging problem because the people captured in surveillance videos often wear similar clothing. Consequently, the differences i...

A Multimodal Authentication for Biometric Recognition System using Intelligent Hybrid Fusion Techniques.

Journal of medical systems
Biometric Recognition and Authentication is used in many applications for the secured identification of the persons. Several Researches has been carried out to strengthen the security algorithms through which the identification can be done in secured...

Task-Oriented Feature-Fused Network With Multivariate Dataset for Joint Face Analysis.

IEEE transactions on cybernetics
Deep multitask learning for face analysis has received increasing attentions. From literature, most existing methods focus on optimizing a main task by jointly learning several auxiliary tasks. It is challenging to consider the performance of each ta...

Arrangements of Resting State Electroencephalography as the Input to Convolutional Neural Network for Biometric Identification.

Computational intelligence and neuroscience
Biometric is an important field that enables identification of an individual to access their sensitive information and asset. In recent years, electroencephalography- (EEG-) based biometrics have been popularly explored by researchers because EEG is ...

A Dynamic Part-Attention Model for Person Re-Identification.

Sensors (Basel, Switzerland)
Person re-identification (ReID) is gaining more attention due to its important applications in pedestrian tracking and security prevention. Recently developed part-based methods have proven beneficial for stronger and explicit feature descriptions, b...

A Novel Technique for Multi Biometric Cryptosystem Using Fuzzy Vault.

Journal of medical systems
Biometric authentication is the process of recognizing a person by means of his\her psychological or behavioral traits. One of the most important issues faced by the biometric system developer is to protect the template obtained from the biometric of...

Multi-Information Flow CNN and Attribute-Aided Reranking for Person Reidentification.

Computational intelligence and neuroscience
This paper presents a multi-information flow convolutional neural network (MiF-CNN) model for person reidentification (re-id). It contains several specific multilayer convolutional structures, where the input and output of a convolutional layer are c...