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Recognizing emotions of a user while interacting with smart devices like tablets and mobile phones is a prospective computer vision problem. They are used in a variety of applications like web browsing, multimedia content playing, gaming, etc., involving human interactions. We present an emotion recognition framework that analyze the facial expressions of a mobile phone user, under various real-world...
In this paper we propose an improvement design to integrate a combination of both a smartphone and a projector to reduce uncomfortable light emitting from a digital projector. The smartphone executes the face detection module, and superimposes the black mask in the position of the face to reduce all uncomfortable light shining in the speaker's eye. This design uses the skin color detection and background...
We propose a method to extract user attributes from the pictures posted in social media feeds, specifically gender information. While traditional approaches rely on text analysis or exploit visual information only from the user profile picture or colors, we propose to look at the distribution of semantics in the pictures coming from the whole feed of a person to estimate gender. In order to compute...
Face analysis is of great interest in the context of digital signage to understand soft biometric of a person. Among the others information gathered from a face, the age of a person is still an open challenging problem. Face representation takes an important role for real time age discrimination. LBP descriptor and the related variants (e.g., CLBP) have been demonstrated to obtain the state-of-the-art...
Face recognition is the process of identification of a person by their facial images. This technique makes it possible to use the facial image of a person to authenticate him into a secure system. Face is the main part of human being to be distinguished from one another. Face recognition system mainly takes an image as an input and compares this image with a number of images stored in database to...
Local Binary Pattern (LBP) is a simple yet robust texture descriptor that has been widely used in many computer vision applications including face recognition. In this paper, we exploit LBP for handwritten Bangla numeral recognition. We classify Bangla digits from their LBP histograms using K Nearest Neighbors (KNN) classifier. The performance of three different variations of LBP - the basic LBP,...
As modern technology evolves, the use of face recognition system is scattering in different sectors of commercial markets rather than in security purposes only. Various approaches are introduced for face recognition system, among them principal component analysis is one of the simplest and efficient method. To improve the performance of face recognition, choosing a threshold value and minimum number...
Recently, state-of-the-art recognition accuracies for pose-invariant face recognition have been achieved by using 2D-Warping methods in a nearest-neighbor framework. However, the main drawback of these methods is the high computational complexity. In this paper we address this issue. We use a simple and fast method to get a rough estimate of a 2D-Warping. This estimate can then be used to apply an...
We propose an efficient linear similarity metric learning method for face verification called Triangular Similarity Metric Learning (TSML). Compared with relevant state-of-the-art work, this method improves the efficiency of learning the cosine similarity while keeping effectiveness. Concretely, we present a geometrical interpretation based on the triangle inequality for developing a cost function...
The existing approaches to automatic emotion analysis rely mostly on visible spectrum data, and very few works have been reported using thermal data for spontaneous facial expression analysis. In this paper, we present a novel infra-red thermal video descriptor in order to improve spontaneous emotion recognition. We first represent each thermal video as a series of clips. The face regions of each...
Subspace segmentation is one of the hottest issues in computer vision and machine learning fields. Generally, data (e.g. face images) are lying in a union of multiple linear subspaces, therefore, it is the key to find a block diagonal affinity matrix, which would result in segmenting data into different clusters correctly. Recently, graph construction based segmentation methods attract lots of attention...
In this paper, we introduce new methods to encode color local texture features for enhanced face representation. In particular, we first propose a novel descriptor; color local phase quantization (CLPQ), which incorporates (channel-wise) unichrome and (cross channel) opponent features in frequency domain. Furthermore, we extend the CLPQ descriptor to multiple scales i.e. multiscale color LPQ (MS-CLPQ),...
This paper investigates the problem of fine-grained face verification under unconstrained conditions. For the conventional face verification task, the verification model is trained with some positive and negative face pairs, where each positive sample pair contains two face images of the same person while each negative sample pair usually consists of two face images from different subjects. However,...
The ability to automatically detect eye center locations in video images allows for estimating gaze direction. This, in turn, facilitates the study of human-computer interaction and behavioral analyses of social interactions. We propose an improved eye center localization method based on the Hough transform, called Circle-based Eye Center Localization (CECL) that is simple, robust, and achieves accuracy...
Facial demographic classification is an attractive topic in computer vision. Attributes such as age and gender can be used in many real life application such as face recognition and internet safety for minors. In this paper, we present a novel approach for age estimation and gender classification under uncontrolled conditions following the standard protocols for fair comparaison. Our proposed approach...
Automatic gender recognition is an emerging problem in computer visions. An accurate gender recognition system can be used to reduce the search space in face recognition system for about half. However, since there is no definitive features of sexual dimorphism on human face that can be applied to all kind of face shapes from any race and age, it needs more studies to optimize the recognition system...
This paper presents a novel method that can estimate the distance of a person up to 6 meters away. The proposed approach is based on face images extracted from a video of a monocular camera through the use of the Viola-Jones approach of OpenCV to detect the faces. The results of the experiments show the practicality of this approach in calculating the distances of the subjects in the camera's view.
Facial expressions are most commonly used for interpretation of human emotion. Over the last few decades, major advances in understanding and analysis of facial expression was achieved by application of computer vision, image processing, and machine learning techniques. In this paper we propose a method to classify facial expression in two classes using the Zernike moments. The proposed system consists...
Sketch recognition is one of the integral components used by law enforcement agencies in solving crime. In recent past, software generated composite sketches are being preferred as they are more consistent and faster to construct than hand drawn sketches. Matching these composite sketches to face photographs is a complex task because the composite sketches are drawn based on the witness description...
A large scale study of the accuracy and efficiency of face detection algorithms on unconstrained face imagery is presented. Nine different face detection algorithms are studied, which are acquired through either government rights, open source, or commercial licensing. The primary data set utilized for analysis is the IAPRA Janus Benchmark A (IJB-A), a recently released unconstrained face detection...
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