Face Recognition with Local Binary Patterns

Abstract

Abstract. In this work, we present a novel approach to face recognition which considers both shape and texture information to represent face images. The face area is first divided into small regions from which Local Binary Pattern (LBP) histograms are extracted and concatenated into a single, spatially enhanced feature histogram efficiently representing the face image. The recognition is performed using a nearest neighbour classifier in the computed feature space with Chi square as a dissimilarity measure. Extensive experiments clearly show the superiority of the proposed scheme over all considered methods (PCA, Bayesian Intra/extrapersonal Classifier and Elastic Bunch Graph Matching) on FERET tests which include testing the robustness of the method against different facial expressions, lighting and aging of the subjects. In addition to its efficiency, the simplicity of the proposed method allows for very fast feature extraction.

A Novel Pedestrian Detector on Low-Resolution Images: Gradient LBP Using Patterns of Oriented Edges

“…The LBPs have shown to be efficient in texture classification [29] and face detection and recognition [27]. It also inspired many pedestrian detection studies as it is intuitive and easy-to-implement [28], [30].…”

“…There has been few works applying the LBP features to object detection frameworks, mainly face recognition [27], [29]. In the original LBP, the goal is to describe every texture and face in a discriminative way, so the LBP threshold was set to 0.…”

A Coarse-to-Fine Classification Scheme for Facial Expression Recognition

“…To overcome their shortcomings, multitemplate pairs and a K nearest neighbor classifier are used in the fine classification. The weighted chi square ( 2 χ ) statistic [12] is defined as follows and will be used in our fine classification later. …”

“…The 256-bin histogram of the labels contains the density of each label over a local region, and can be used as a texture descriptor of the region. Recently, an LBP based facial representation has shown an outstanding result in face recognition [12]. In our work, we use a similar facial representation as that proposed in [12]:…”

“…Recently, an LBP based facial representation has shown an outstanding result in face recognition [12]. In our work, we use a similar facial representation as that proposed in [12]:…”