An Approach for Pose Invariant Face Recognition System Using Log-Gabor Feature
نویسندگان
چکیده
منابع مشابه
Feature Selection for Pose Invariant Face Recognition
One of the major difficulties in face recognition systems is the in-depth pose variation problem. Most face recognition approaches assume that the pose of the face is known. In this work, we have designed a feature based pose estimation and face recognition system using 2D Gabor wavelets as local feature information. The difference of our system from the existing ones lies in its simplicity and...
متن کاملAn Efficient Pose Invariant Face Recognition System
This paper proposes an efficient face recognition system which is invariant to pose. It presents a transformation to generate features of the frontal face from a given posed image of a subject. The proposed system has been tested on three databases viz. IITK, FERET and CMU-PIE. It has been observed that it performs better than the existing well known system.
متن کامل3D Face Recognition using Log-Gabor Templates
The use of Three Dimensional (3D) data allows new facial recognition algorithms to overcome factors such as pose and illumination variations which have plagued traditional 2D Face Recognition. In this paper a new method for providing insensitivity to expression variation in range images based on Log-Gabor Templates is presented. By decomposing a single image of a subject into 147 observations t...
متن کاملAutomatic Frontal Face Reconstruction Approach for Pose Invariant Face Recognition
Handling pose variations for face recognition system is a challenging task. The recognition rate is drastically decreasing with the images captured in uncontrolled environment having pose variations in yaw, pitch and roll angles. When the face image with frontal pose it is proved that the recognition system performs well. In this research an attempt is made to reconstruct frontal pose face imag...
متن کاملFeature Reconstruction Disentangling for Pose-invariant Face Recognition Supplementary Material
Pose-variant face generation We designed a network to predict 3DMM parameters from a single face image. The design is mainly based on VGG16 [4]. We use the same number of convolutional layers as VGG16 but replacing all max pooling layers with stride-2 convolutional operations. The fully connected (fc) layers are also different: we first use two fc layers, each of which has 1024 neurons, to conn...
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: IOP Conference Series: Materials Science and Engineering
سال: 2020
ISSN: 1757-899X
DOI: 10.1088/1757-899x/925/1/012030