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Systems for still-to-video face recognition (FR) are typically used to detect target individuals in watch-list screening applications. These surveillance applications are challenging because the appearance of faces change according to capture conditions, and very few reference stills are available a priori for enrollment. To improve performance, an adaptive appearance model tracker (AAMT) is proposed...
In this paper, we propose an efficient expression-invariant 3D face recognition algorithm to compute the minimum-distortion mapping between two 3D face by the Generalized MultiDimensional Scaling (GMDS). Both full and partial parts matching are computed for finding the least distortion embedding of one 3D face into another during GMDS. The problem of expression-invariant three-dimensional face recognition...
This paper presents an automated system to increase the security and surveillance of ATM kiosks. Due to the increase of robbery in ATM kiosks, it is important to employ an automated surveillance system to protect and secure the ATM machine from threats. Currently, a camera attached with the ATM unit, records and transmits the video feed to the main server of the bank. Around the clock, this manual...
In this paper, we develop a spatio-temporal cascade shape regression (STCSR) model for robust facial shape tracking. It is different from previous works in three aspects. Firstly, a multi-view cascade shape regression (MCSR) model is employed to decrease the shape variance in shape regression model construction, which is able to make the learned regression model more robust to shape variances. Secondly,...
Generic face detection and facial landmark localization in static imagery are among the most mature and well-studied problems in machine learning and computer vision. Currently, the top performing face detectors achieve a true positive rate of around 75-80% whilst maintaining low false positive rates. Furthermore, the top performing facial landmark localization algorithms obtain low point-to-point...
Being the most distinct feature point in 3D facial landmarks, nose tip plays a significant role in 3D facial studies such as face detection, face recognition, facial features extraction, face alignment, etc. Successful detection of nose tip can facilitate many tasks of 3D facial studies. In this paper, we propose a novel method to detect nose tip robustly. The method is robust to noise, needs not...
Various watermarking schemes achieved the robustness against the usual operations such as simplification, remeshing and noise addition. However, the techniques were not robust against cropping, nevertheless the cropping attack is commonly performed by general editing. In this paper, we propose a robust 3D mesh watermarking method against cropping. We achieve the blind watermarking scheme involving...
Many research works have been done in face recognition during the last years that indicates the importance of face recognition systems in many applications including identity authentication. In this paper we propose an approach for face recognition which is suitable for unconstrained image acquisition and has a low computational cost. Since in practical applications such as in smartphones, imaging...
Apparent age estimation from face image has attracted more and more attentions as it is favorable in some real-world applications. In this work, we propose an end-to-end learning approach for robust apparent age estimation, named by us AgeNet. Specifically, we address the apparent age estimation problem by fusing two kinds of models, i.e., real-value based regression models and Gaussian label distribution...
In this paper we introduce a new dataset and pose invariant sampling method and describe the ensemble methods used for recognizing faces in 3D scenes, captured using commodity depth sensors. We use the 3D SIFT key point detector to take advantage of the similarities between faces, which leads to a set of points of interest based on the curvature of the face. For all key points, features are extracted...
This paper presents a novel facial expression recognition approach in the presence of partial occlusion using Gabor filters and gray-level co-occurrence matrix (GLCM). At first, we design an algorithm to extract the block Gabor feature statistics according to the spatial distribution of the face organ. Then, GLCM is firstly introduced into expression recognition field to make up for the deficiency...
This manuscript present a gender classification technique uses the (2D)2PCA, Gabor filter, and SVM for classifying the gender from occluded and non occluded face images. Present work explores two approaches, i.e., Fusion at feature level, and fusion at classifier level. Experimental result shows that, both the proposed approaches give an acceptable result on non-occluded face image database. For occlude...
We consider the problem of robust face recognition in which both the training and test samples might be corrupted because of disguise and occlusion. Performance of conventional subspace learning methods and recently proposed sparse representation based classification (SRC) might be degraded when corrupted training samples are provided. In addition, sparsity based approaches are time-consuming due...
Local ternary pattern (LTP) is a noise-robust version of local binary pattern (LBP). They are both encoding for the differences between the intensity of the center pixel and its neighborhoods. In this paper, based on Webers law we propose two new local descriptors, named Weber binary pattern (WBP) and Weber ternary pattern (WTP), which utilize binary and ternary encoding separately for the evaluation...
As the most distinct feature point in facial landmarks, nose tip plays a significant role in 3D facial studies. Successful detection of nose tip can facilitate many 3D facial studies tasks. In this paper, we propose a novel method to detect nose tip robustly. The method is robust to noise, need not training, can handle large rotations and occlusions. We first remove small isolated connected regions...
In this paper, we present a multi-stage regression-based approach for the 300 Videos in-the-Wild (300-VW) Challenge, which progressively initializes the shape from obvious landmarks with strong semantic meanings, e.g. eyes and mouth corners, to landmarks on face contour, eyebrows and nose bridge which have more challenging features. Compared with initialization based on mean shape and multiple random...
The Gabor filters are considered one of the best image representation approaches for face recognition (FR). Researchers have exploited various configurations of Gabor magnitude as well as Gabor phase responses and their modeling with other descriptors. In this paper, we propose a novel face representation approach; Local Gabor Rank Pattern (LGRP), which exploits ordinal ranking of Gabor response images...
In case of disasters such as cyclones, earthquakes, severe floods etc., widespread damages to infrastructures such as power grid, communication infrastructure etc. is commonplace. Especially to power grid, the damages to various structures are typically spread out in wide areas. Usage of drones to do fast remote survey of damage area is gaining popularity. From the remote surveillance video of any...
Recently, nuclear norm based matrix regression (NMR) for classification has been proposed to characterize the whole structure of the error image. However, NMR ignores both the label information and the group structure of training samples. This paper presents a novel yet effective coding scheme called locality-constrained group sparse coding regularized NMR (LGNMR) which not only overcomes these limitations...
Recently sparse and collaborative representation based classification has been developed for face recognition with single sample per person (SSPP). By using variations extracted from a generic training set as an additional common dictionary, promising performance has been reported in face recognition with SSPP. However, existing representation based classifiers for face recognition with SSPP ignored...
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