The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Facial expressions play an important role in communication. Impaired facial expression is a common sign of numerous medical conditions, particularly neurological disorders. Accurate automated systems are needed to recognize facial expressions and to reveal valuable information that can be used for diagnosis and monitoring of neurological disorders. This paper presents a novel deep learning approach...
We consider the problem of face swapping in images, where an input identity is transformed into a target identity while preserving pose, facial expression and lighting. To perform this mapping, we use convolutional neural networks trained to capture the appearance of the target identity from an unstructured collection of his/her photographs. This approach is enabled by framing the face swapping problem...
Command extraction from human beings becomes easier for a machine if it can analyze the non verbal ways of communication such as emotions. This paper focuses on improving the efficiency of extracting emotion from human facial expression images. The features that were extracted in this experiment were obtained from JAFFE (Japanese Female Facial Expression) database which includes 213 images of different...
The aim of this work is to explore the usefulness of face semantic segmentation for head pose estimation. We implement a multi-class face segmentation algorithm and we train a model for each considered pose. Given a new test image, the probabilities associated to face parts by the different models are used as the only information for estimating the head orientation. A simple algorithm is proposed...
Selfies have become commonplace. More and more people take pictures of themselves, and enjoy enhancing these pictures using a variety of image processing techniques. One specific functionality of interest is automatic skin and hair segmentation, as this allows for processing one's skin and hair separately. Traditional approaches require user input in the form of fully specified trimaps, or at least...
Face editing has a variety of applications, especially with the increasing popularity of photography using mobile devices. In this work, we argue that the performance of face image editing can be further improved by using semantic segmentation which marks each pixel with a label that indicates its corresponding facial part. To this end, we propose a deep learning based method for automatic pixel-level...
Artificial neural networks (ANN) are one of the dominant learning techniques used in the field of artificial intelligence and have significant assets as their properties imitate the behavior of neurons in human brain. In this paper is presented the research focused on ANN, specifically Multilayer perceptron (MPL) with the aim of detection of human face in the still image. This system was implemented...
In order to further improve the recognition rate and computing efficiency of modular 2DPCA in face recognition, an improved modular 2DPCA method based on image segmentation is proposed. Firstly, segmentation of threshold value optimization is utilized to segment face image of training samples into several non-overlapping sub-image spaces so that the pixel number has uniform distribution in each sub-image...
Face image analysis continues as an ongoing challenge in biometrics and image processing due to the state variations of facial elements. In this context, the mouth-state plays a fundamental role because its impact on the perception of facial gestures. Current work on mouth-state detection is mainly focused on the creation of classifiers derived from large training datasets. This technique requires...
Skin segmentation can effectively improve accuracy of face searching in a picture. However, it is a difficult problem to segment face skin from a photo with complex background. In this paper, a novel coupled template for face regions extraction after skin segmentation is proposed to overcome the difficulty that face regions are largely sticky to similar skin backgrounds. The algorithm based on the...
Deep learning models can obtain state-of-the-art performance across many speech and image processing tasks, often significantly outperforming earlier methods. In this paper, we attempt to further improve the performance of these models by introducing multi-task training, in which a combined deep learning model is trained for two inter-related tasks. We show that by introducing a secondary task (such...
Aiming to the issue of face recognition with partial contiguous occlusion, a new face recognition method was proposed by removing the outlier area in this paper. A mean face image is firstly obtained from train images, which is subtracted by the test face to form an error face image. Then the error face image is used to obtain the occlusion area of the test image by image segmentation technique, and...
This paper presents a method for estimating color face images from near-infrared monochrome face images. This estimation is done by the regression from a monochrome image to a color image. One difficult problem is that the regression depends on face organs. That is, the same intensity pixels in an infrared monochrome image do not correspond to the same color pixels. Therefore, entirely uniform regression...
In the real-world unconstrained face recognition scenarios, automatic facial landmarking scheme using the active shape model (ASM) usually gives non-ideal results, especially at the facial boundary. This is because the local subspace methods such as the principal component analysis (PCA) used in the ASM does not properly discern skin texture and background with very similar photometric and textual...
Hair segmentation is challenging due to the diverse appearance, irregular region boundary and the influence of complex background. To deal with this problem, we propose a novel method, named Isomorphic Manifold Inference (IMI). Given a head-shoulder image, a Coarse Hair Probability Map (Coarse HPM), each element of which represents the probability of the pixel being hair, is initially calculated by...
This paper investigates how to parse (segment) facial components from face images which may be partially occluded. We propose a novel face parser, which recasts segmentation of face components as a cross-modality data transformation problem, i.e., transforming an image patch to a label map. Specifically, a face is represented hierarchically by parts, components, and pixel-wise labels. With this representation,...
This paper has proposed an improved algorithm of face detction by the combination of the respective characteristics of Adaboost algorithm and the skin color segmentation algorithm. Face candidate regions were first obtained by the means of skin color detection, which were then input as the trained Adaboost cascade classifier to get accurate and quick face location. Also, in this paper the strategy...
Human face detection has become a major field of interest in current research because there is no deterministic algorithm to find face(s) in a given image. Further the algorithms that exist are very much specific to the kind of images they would take as input and detect faces. The problem is to detect faces in the given, colored group photograph. In this paper, an improved segmentation algorithm for...
The research of object localization is active in the field of visual object category. In this paper, we focus on object localization in a given special category dataset. We propose to exploit the context aware category discovery for object localization without any labeled examples. Firstly, the image is segmented based on a multiple segmentation algorithm. Secondly, these generated regions are clustered...
This paper provides an example of the face recognition using PCA method and impact of segmentation algorithm ‘Belief Propagation’ on recognition rate. Principle component analysis (PCA) is a multivariate technique that analyzes a face data in which observation are described by several inter-correlated dependent variables. The goal is to extract the important information from the face data, to represent...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.