Hierarchical Wavelet Networks for Facial Feature Localization
ثبت نشده
چکیده
We present a technique for facial feature localization using a two-level hierarchical wavelet network. The first level wavelet network is used for face matching, and yields an affine transformation used for a rough approximation of feature locations. Second level wavelet networks for each feature are then used to fine-tune the feature locations. Construction of a training database containing hierarchical wavelet networks of many faces allows features to be detected in most faces. Experiments show that facial feature localization benefits significantly from the hierarchical approach. Results compare favorably with existing techniques for feature localization.
منابع مشابه
Hierarchical Wavelet Networks for Facial Feature Localization
We present a technique for facial feature localization using a two-level hierarchical wavelet network. The first level wavelet network is used for face matching, and yields an affine transformation used for a rough approximation of feature locations. Second level wavelet networks for each feature are then used to fine-tune the feature locations. Construction of a training database containing hi...
متن کاملFacial Feature Detection Using A Hierarchical Wavelet Face Database
WaveBase is a system for detecting features in a face image. It has a database of faces, each with a two-level hierarchical wavelet network. When a new face image is presented to the system for face detection, WaveBase searches its database for the “best face” – the face whose first level wavelet network most closely matches the new face. It also determines an affine transformation to describe ...
متن کاملIntroducing a method for extracting features from facial images based on applying transformations to features obtained from convolutional neural networks
In pattern recognition, features are denoting some measurable characteristics of an observed phenomenon and feature extraction is the procedure of measuring these characteristics. A set of features can be expressed by a feature vector which is used as the input data of a system. An efficient feature extraction method can improve the performance of a machine learning system such as face recognit...
متن کاملA Fast Localization and Feature Extraction Method Based on Wavelet Transform in Iris Recognition
With an increasing emphasis on security, automated personal identification based on biometrics has been receiving extensive attention. Iris recognition, as an emerging biometric recognition approach, is becoming a very active topic in both research and practical applications. In general, a typical iris recognition system includes iris imaging, iris liveness detection, and recognition. This rese...
متن کاملAN INTELLIGENT FAULT DIAGNOSIS APPROACH FOR GEARS AND BEARINGS BASED ON WAVELET TRANSFORM AS A PREPROCESSOR AND ARTIFICIAL NEURAL NETWORKS
In this paper, a fault diagnosis system based on discrete wavelet transform (DWT) and artificial neural networks (ANNs) is designed to diagnose different types of fault in gears and bearings. DWT is an advanced signal-processing technique for fault detection and identification. Five features of wavelet transform RMS, crest factor, kurtosis, standard deviation and skewness of discrete wavelet co...
متن کامل