Quantifying appearance retention in carpets using geometrical local binary patterns

Quality assessment in carpet manufacturing is performed by humans who evaluate the appearance retention (AR) grade on carpet samples. To quantify the AR grades objectively, different research based on computer vision have been developed. Among them Local Binary Pattern (LBP) and its variations has shown promising results. Nevertheless, the requirements of quality assessment on a wide range of carpets have not been met yet. One of the difficulties is to distinguish between consecutive AR grades in carpets. For this, we adopt an extension of LBP called Geometrical Local Binary Patterns (GLBP) that we recently proposed. The basis of GLBP is to evaluate the grey scale differences between adjacent points defined on a path in a neighbourhood. Symmetries of the paths in the GLBPs are evaluated. The proposed technique is compared with an invariant rotational mirror based LBP technique. The results show that the GLBP technique performs better to distinguish consecutive AR grades in carpets

Kaposi's sarcoma herpesvirus-induced endothelial cell reprogramming supports viral persistence and contributes to Kaposi's sarcoma tumorigenesis

Kaposi's sarcoma (KS) is an endothelial tumor causally linked to Kaposi's sarcoma herpesvirus (KSHV) infection. At early stages of KS, inflammation and aberrant neoangiogenesis are predominant, while at late stages the disease is characterized by the proliferation of KSHV-infected spindle cells (SC). Since KSHV infection modifies the endothelial cell (EC) identity, the origin of SCs remains elusive. Yet, pieces of evidence indicate the lymphatic origin. KSHV-infected ECs display increased proliferative, angiogenic and migratory capacities which account for KS oncogenesis. Here we propose a model in which KSHV reprograms the EC identity, induces DNA damage and establishes a dysregulated gene expression program involving interplay of latent and lytic genes allowing continuous. reinfection of ECs attracted to the tumor by the secretion of virus-induced cellular factors.Peer reviewe

A good balance of costs and benefits: convincing a university administration to support the installation of an interactive multi-application display system on campus

Interactive digital signage systems allow passers-by to take (temporary) control of a public display in order to select content and applications of interest, or even upload content of their own. Not surprisingly, display owners are hesitant to embrace such interactivity, given the uncertainty of what will be shown on their displays. In this paper we summarize our experience of deploying an interactive multi-application display system in the context of a university environment, and in particular our engagements with display owners (i.e., university administration) in order to convince them and get their support for the installation and deployment of such a system. We present the results of semi-structured interviews with display owners regarding their motivations, needs, and concerns with respect to the deployment of such a system at our university. While one cannot generalize from our results, we nevertheless believe that our experiences offer helpful advice to developers of such systems (and/or researchers interested in designing and studying them) in order to aid them in successfully gathering the support of these important stakeholders

An edge-based approach for robust foreground detection

Foreground segmentation is an essential task in many image processing applications and a commonly used approach to obtain foreground objects from the background. Many techniques exist, but due to shadows and changes in illumination the segmentation of foreground objects from the background remains challenging. In this paper, we present a powerful framework for detections of moving objects in real-time video processing applications under various lighting changes. The novel approach is based on a combination of edge detection and recursive smoothing techniques.We use edge dependencies as statistical features of foreground and background regions and define the foreground as regions containing moving edges. The background is described by short- and long-term estimates. Experiments prove the robustness of our method in the presence of lighting changes in sequences compared to other widely used background subtraction techniques

Multifrequency Observations of the Gamma-Ray Blazar 3C 279 in Low-State during Integral AO-1

We report first results of a multifrequency campaign from radio to hard X-ray energies of the prominent gamma-ray blazar 3C 279 during the first year of the INTEGRAL mission. The variable blazar was found at a low activity level, but was detected by all participating instruments. Subsequently a multifrequency spectrum could be compiled. The individual measurements as well as the compiled multifrequency spectrum are presented. In addition, this 2003 broadband spectrum is compared to one measured in 1999 during a high activity period of 3C 279.Comment: 4 pages including 6 figures, to appear in: 'Proc. of the 5th INTEGRAL Workshop', ESA SP-552, in pres

A Family of Maximum Margin Criterion for Adaptive Learning

In recent years, pattern analysis plays an important role in data mining and recognition, and many variants have been proposed to handle complicated scenarios. In the literature, it has been quite familiar with high dimensionality of data samples, but either such characteristics or large data have become usual sense in real-world applications. In this work, an improved maximum margin criterion (MMC) method is introduced firstly. With the new definition of MMC, several variants of MMC, including random MMC, layered MMC, 2D^2 MMC, are designed to make adaptive learning applicable. Particularly, the MMC network is developed to learn deep features of images in light of simple deep networks. Experimental results on a diversity of data sets demonstrate the discriminant ability of proposed MMC methods are compenent to be adopted in complicated application scenarios.Comment: 14 page

Multi-resolution texture classification based on local image orientation

The aim of this paper is to evaluate quantitatively the discriminative power of the image orientation in the texture classification process. In this regard, we have evaluated the performance of two texture classification schemes where the image orientation is extracted using the partial derivatives of the Gaussian function. Since the texture descriptors are dependent on the observation scale, in this study the main emphasis is placed on the implementation of multi-resolution texture analysis schemes. The experimental results were obtained when the analysed texture descriptors were applied to standard texture databases

Surface reconstruction of wear in carpets by using a wavelet edge detector

Carpet manufacturers have wear labels assigned to their products by human experts who evaluate carpet samples subjected to accelerated wear in a test device. There is considerable industrial and academic interest in going from human to automated evaluation, which should be less cumbersome and more objective. In this paper, we present image analysis research on videos of carpet surfaces scanned with a 3D laser. The purpose is obtaining good depth Images for an automated system that should have a high percentage of correct assessments for a wide variety of carpets. The innovation is the use of a wavelet edge detector to obtain a more continuously defined surface shape. The evaluation is based on how well the algorithms allow a good linear ranking and a good discriminance of consecutive wear labels. The results show an improved linear ranking for most carpet types, for two carpet types the results are quite significant

Proxemic Flow: Dynamic Peripheral Floor Visualizations for Revealing and Mediating Large Surface Interactions

Interactive large surfaces have recently become commonplace for interactions in public settings. The fact that people can engage with them and the spectrum of possible interactions, however, often remain invisible and can be confusing or ambiguous to passersby. In this paper, we explore the design of dynamic peripheral floor visualizations for revealing and mediating large surface interactions. Extending earlier work on interactive illuminated floors, we introduce a novel approach for leveraging floor displays in a secondary, assisting role to aid users in interacting with the primary display. We illustrate a series of visualizations with the illuminated floor of the Proxemic Flow system. In particular, we contribute a design space for peripheral floor visualizations that (a) provides peripheral information about tracking fidelity with personal halos, (b) makes interaction zones and borders explicit for easy opt-in and opt-out, and (c) gives cues inviting for spatial movement or possible next interaction steps through wave, trail, and footstep animations. We demonstrate our proposed techniques in the context of a large surface application and discuss important design considerations for assistive floor visualizations

Topological descriptors for 3D surface analysis

We investigate topological descriptors for 3D surface analysis, i.e. the classification of surfaces according to their geometric fine structure. On a dataset of high-resolution 3D surface reconstructions we compute persistence diagrams for a 2D cubical filtration. In the next step we investigate different topological descriptors and measure their ability to discriminate structurally different 3D surface patches. We evaluate their sensitivity to different parameters and compare the performance of the resulting topological descriptors to alternative (non-topological) descriptors. We present a comprehensive evaluation that shows that topological descriptors are (i) robust, (ii) yield state-of-the-art performance for the task of 3D surface analysis and (iii) improve classification performance when combined with non-topological descriptors.Comment: 12 pages, 3 figures, CTIC 201