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Limited By:	Subject = face recognition;

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Displaying Results 1 - 6 of 6 on page 1 of 1

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A hybrid technique for face detection in color images (2005)

Cooray, Saman H.; O'Connor, Noel E.

A hybrid technique for face detection in color images (2005)

Cooray, Saman H.; O'Connor, Noel E.

Abstract:

In this paper, a hybrid technique for face detection in color images is presented. The proposed technique combines three analysis models, namely skin detection, automatic eye localization, and appearance-based face/nonface classification. Using a robust histogram-based skin detection model, skin-like pixels are first identified in the RGB color space. Based on this, face bounding-boxes are extracted from the image. On detecting a face bounding-box, approximate positions of the candidate mouth feature points are identified using the redness property of image pixels. A region-based eye localization step, based on the detected mouth feature points, is then applied to face bounding-boxes to locate possible eye feature points in the image. Based on the distance between the detected eye feature points, face/non-face classification is performed over a normalized search area using the Bayesian discriminating feature (BDF) analysis method. Some subjective evaluation results are presented on ...

http://doras.dcu.ie/235/

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A unified system for segmentation and tracking of face and hands in sign language recognition (2006)

Awad, George M.; Han, Junwei; Sutherland, Alistair

A unified system for segmentation and tracking of face and hands in sign language recognition (2006)

Awad, George M.; Han, Junwei; Sutherland, Alistair

Abstract:

This paper presents a unified system for segmentation and tracking of face and hands in a sign language recognition using a single camera. Unlike much related work that uses colour gloves, we detect skin by combining 3 useful features: colour, motion and position. These features together, represent the skin colour pixels that are more likely to be foreground pixels and are within a predicted position range. We extend the previous research in occlusion detection to handle occlusion between any of the skin objects using a Kalman filter based algorithm. The tracking improves the segmentation by reducing the search space and the segmentation enhances the overall tracking process. The algorithm is tested on several video sequences from a standard database and can provide a very low error rate

http://doras.dcu.ie/225/

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Authentication based on face recognition under uncontrolled conditions (2017)

Tavakolian, Niloofar; Nazemi, Azadeh; Azimifar, Zohreh

Authentication based on face recognition under uncontrolled conditions (2017)

Tavakolian, Niloofar; Nazemi, Azadeh; Azimifar, Zohreh

Abstract:

This paper describes a method to address is- sues regarding uncontrolled conditions in face recognition. This method using mask projection, extracts affecting factor from the test sample and adds it to all normal training samples then compares test sample with all synthetic affected training samples. The method has been applied for multi-factor authentication/verification based on face biometric. Obtained results indicate high accuracy in the lake of sufficient training samples for each class(single sample classes). of the claimed user.

http://doras.dcu.ie/23042/

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Enhancing person annotation for personal photo management applications (2009)

Cooray, Saman H.; O'Connor, Noel E.

Enhancing person annotation for personal photo management applications (2009)

Cooray, Saman H.; O'Connor, Noel E.

Abstract:

This paper addresses a sub-problem of the broad annotation problem, namely "person annotation", associated with personal digital photo management and investigates approaches to enhancing person annotation in personal photo management applications. We study a number of approaches to enhance the performance of semi-automatic person annotation using real-life personal photo collections as the test data. To this end, face and body-patch features are employed to describe the appearance of a person as a means to more effectively capture the identities of re-appearing people in personal photo archives. Experiments are carried out to identify a suitable initial annotation method, compare the performances of event-constrained person matching with global person matching, and the effect of the size of initial annotation on the overall performance of person annotation in real-life personal photo archives. The evaluation results, presented in terms of H-Hit rate figures, illustrate tha...

http://doras.dcu.ie/14799/

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Estimation of the Temporal Dynamics of Posed and Spontaneous Facial Expression Formation Using LLE (2009)

Delannoy, Jane Reilly; McDonald, John

Estimation of the Temporal Dynamics of Posed and Spontaneous Facial Expression Formation Using LLE (2009)

Delannoy, Jane Reilly; McDonald, John

Abstract:

When analysing facial expressions, it is not only the final expression itself, but also its formation that plays an important role when attempting to decipher its meaning. Currently in research there are two techniques for describing the dynamics of facial expression; quantitative and temporal based analysis. Quantitative-based techniques attempt to determine the amplitude of the expression in terms of intensity levels, where the levels correspond to some measure of the extent to which the expression is present on the face. Temporal-based techniques split the expression into three temporal phases (onset-apex-offset). In this paper we focus on the temporal aspects of facial expression formation, describing our research into applying a non-linear manifold extraction technique for modelling these temporal phases. We present initial results of our technique for modelling the temporal aspects of both posed and spontaneous facial expressions.

http://mural.maynoothuniversity.ie/8335/

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Non-Linear Approaches for the Classification of Facial Expressions at Varying Degrees of Intensity (2007)

Reilly, Jane; Ghent, John; McDonald, John

Non-Linear Approaches for the Classification of Facial Expressions at Varying Degrees of Intensity (2007)

Reilly, Jane; Ghent, John; McDonald, John

Abstract:

The research discussed in this paper documents a comparative analysis of two nonlinear dimensionality reduction techniques for the classification of facial expressions at varying degrees of intensity. These nonlinear dimensionality reduction techniques are Kernel Principal Component Analysis (KPCA) and Locally Linear Embedding (LLE). The approaches presented in this paper employ psychological tools, computer vision techniques and machine learning algorithms. In this paper we concentrate on comparing the performance of these two techniques when combined with Support Vector Machines (SVMs) at the task of classifying facial expressions across the full expression intensity range from near-neutral to extreme facial expression. Receiver Operating Characteristic (ROC) curve analysis is employed as a means of comprehensively comparing the results of these techniques.

http://mural.maynoothuniversity.ie/8345/

Displaying Results 1 - 6 of 6 on page 1 of 1