Centralized Gradient Pattern for Face Recognition

3D Face Recognition using Patch Geodesic Derivative Pattern

In this paper, a novel Patch Geodesic Derivative Pattern (PGDP) describing the texture map of a face through its shape data is proposed. Geodesic adjusted textures are encoded into derivative patterns for similarity measurement between two 3D images with different pose and expression variations. An extensive experimental investigation is conducted using the publicly available Bosphorus and BU-3...

Face Recognition via Centralized Coordinate Learning

Owe to the rapid development of deep neural network (DNN) techniques and the emergence of large scale face databases, face recognition has achieved a great success in recent years. During the training process of DNN, the face features and classification vectors to be learned will interact with each other, while the distribution of face features will largely affect the convergence status of netw...

Local gradient pattern - A novel feature representation for facial expression recognition

Many researchers adopt Local Binary Pattern for pattern analysis. However, the long histogram created by Local Binary Pattern is not suitable for large-scale facial database. This paper presents a simple facial pattern descriptor for facial expression recognition. Local pattern is computed based on local gradient flow from one side to another side through the center pixel in a 3x3 pixels region...

Image Gradient Regression Approach for Face Recognition

This paper represents a robust face recognition system. The proposed face recognition system consist is useful in forming an effective face recognition. Proposed method overcomes the problem of multi collinearity and also give good results in case of small sample size (SSS) problem . In Image Gradient Regression Approach (IGRA), first in preprocessing stage image is transformed by normalizing g...

Multidirectional Binary Pattern for Face Recognition