In this work, we propose a novel approach to recognize facial expressions from static images. First, the local binary patterns (LBP) are used to efficiently represent the facial images and then the linear programming (LP) technique is adopted to classify seven facial expressions—anger, disgust, fear, happiness, sadness, surprise, and neutral. Experimental results demonstrate an average recognit...

Research in automatic facial expression recognition has permitted the development of systems discriminating between the six prototypical expressions, i.e. anger, disgust, fear, happiness, sadness and surprise, in frontal video sequences. Achieving high recognition rate often implies high computational costs that are not compatible with real time applications on limited-resource platforms. In or...

We present a description of our approach for the “Bird task Identification LifeCLEF 2014”. Our approach consists of four stages: (1) a filtering stage for the filtering of audio bird recordings; (2) segmentation stage for the extraction of syllables; (3) a candidate generation based on HOG features from the syllables using SVM; and (4) a species identification using a Sparse Representation-base...

In this chapter, we propose two novel and curvature-free features: run-lengths of Local Binary Pattern (LBPruns) and Cloud Of Line Distribution (COLD) features for writer identification. The LBPruns is the joint distribution of the traditional run-length and local binary pattern (LBP) methods, which computes the run-lengths of local binary patterns on both binarized images and gray scale images...

0167-8655/$ see front matter 2011 Elsevier B.V. A doi:10.1016/j.patrec.2011.05.016 E-mail address: [email protected] Gender recognition is one of fundamental face analysis tasks. Most of the existing studies have focused on face images acquired under controlled conditions. However, real-world applications require gender classification on real-life faces, which is much more challenging du...

This paper presents a comparative analysis of binary patterns for gender classification with a novel method of feature transformation for improved accuracy rates. The main requirements of our application are speed and accuracy. We investigate a combination of local binary patterns (LBP), Census Transform (CT) and Modified Census Transform (MCT) applied over the full, top and bottom halves of th...

This paper presents several novel Gabor-based color descriptors for object and scene image classification. Firstly, a new Gabor-HOG descriptor is proposed for image feature extraction. Secondly, the Gabor-LBP descriptor derived by concatenating the Local Binary Patterns (LBP) histograms of all the component images produced by applying Gabor filters is integrated with the Gabor-HOG using an opti...

In this paper subpattern-based approaches are used to solve the age classification problem on facial images. Subpattern-based approaches named Local Binary Patterns (LBP), subpattern-based Principal Component Analysis (spPCA) and modular Principal Component Analysis (mPCA) are examined to demonstrate the age classification performance on female and male facial images of human beings with severa...

This paper presents a new approach for the classification of pathological vs. healthy endomicroscopic images of the alveoli. These images, never seen before, require an adequate description. We investigate two types of feature vector for discrimination: a high-level feature vector based on visual analysis of the images, and a pixel-based, generic feature vector, based on Local Binary Patterns (...

many researchers adopt local binary pattern for pattern analysis. however, the long histogram created by local binary pattern is not suitable for large-scale facial database. this paper presents a simple facial pattern descriptor for facial expression recognition. local pattern is computed based on local gradient flow from one side to another side through the center pixel in a 3x3 pixels region...