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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...
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...
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...
Face segmentation is a first step for face biometric systems. In this paper we present a face segmentation algorithm for thermographic images. This algorithm is compared with the classic Viola and Jones algorithm used for visible images. Experimental results reveal that, when segmenting a multispectral (visible and thermal) face database, the proposed algorithm is more than 10 times faster, while...
The influence of age progression on the performance of face verification systems is a challenging and largely open research problem. When only one reference and one test image per subject are available, in this paper we propose to manage the aging influence on the adult face verification system through a score-age stacking technique to find the global decision boundary which can change across the...
This paper introduces a novel shape model, Sparse Representation Shape Model (SRSM). Rather than for modeling specific deformable shapes, this model is specially designed for shape segmentation and matching. This model is utilized under the framework of Active Shape Models (ASM). Unlike the Linear Point Distribution Model utilized by original ASM, which relies on obscure statistical boundary to do...
In this paper we present pre-processing steps and a voting scheme that improve the effectiveness of the spectroface approach. It consists on a series of pre-processing steps prior to spectroface together with a texture feature that are used independently. The classifier output for each of the 13 features is fused using a majority voting scheme coupled with rules for ties and strong features. Yale...
We propose in this paper a search approach which aim to improve identification in biometric databases. We work with face images and we develop appearance-based Eigenfaces and Fisherfaces methods to generate holistic and discriminant features and attributes. These features, which describe faces, are often used to establish the required identity in a classical identification process. In this work we...
Fully automated image segmentation is an essential step for designing automated identification systems. In this paper, we address the problem of fully automated image segmentation in the context of ear biometrics. Our segmentation approach achieves more than 90% accuracy based on three different sets of 3750 facial images for 376 persons. We also present an approach for the automated evaluation of...
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