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—Local binary pattern (LBP) is a nonparametric de-scriptor, which efficiently summarizes the local structures of images. In recent years, it has aroused increasing interest in many areas of image processing and computer vision and has shown its effectiveness in a number of applications, in particular for facial image analysis, including tasks as diverse as(More)
This paper introduces a knowledge-driven approach to real-time, continuous activity recognition based on multisensor data streams in smart homes. The approach goes beyond the traditional data-centric methods for activity recognition in three ways. First, it makes extensive use of domain knowledge in the life cycle of activity recognition. Second, it uses(More)
automatic analysis may have many applications such as smart human-computer interactions or multimedia indexing. Main difficulties for an efficient speech emotion classification reside in complex emotional class borders leading to necessity of appropriate audio feature selection. While current work in the literature only relies on classical frequency and(More)
This paper presents a robust eye detection algorithm for gray intensity images. The idea of our method is to combine the respective advantages of two existing techniques, feature based method and template based method, and to overcome their shortcomings. Firstly, after the location of face region is detected, a feature based method will be used to detect(More)
—In this study, we present a novel geometric representation for 3D faces in order to enhance distinctiveness of generally smooth range images. This novel face representation is based on Multi-Scale Extended Local Binary Patterns (ELBP) and enables accurate and fast description of local shape variations on range faces. When associated with the proposed(More)
3D face landmarking aims at automatic localization of 3D facial features and has a wide range of applications, including face recognition, face tracking, facial expression analysis. Methods so far developed for pure 2D texture images were shown sensitive to lighting condition changes. In this paper, we present a statistical model-based technique for(More)
—In this paper, we propose a novel face recognition approach based on 2.5D/3D shape matching. While most of existing methods use facial intensity image, we aim to develop a method using three-dimensional information of the human face. This is the main innovation of our technology. In our approach, the 3D dimensional information is introduced in order to(More)
Purpose –This paper aims to serve two main purposes. In the first instance it aims to it provide an overview addressing the state-of-the-art in the area of activity recognition, in particular, in the area of object-based activity recognition. This will provide the necessary material to inform relevant research communities of the latest developments in this(More)