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

Kestävät jalat - kettujen jalkaterveyden kehityshanke. Raportti nro 3

Luken kirjat, raportit, oppaat ja esitteet. Raportti nro 3201

Expanding the Family of Grassmannian Kernels: An Embedding Perspective

Modeling videos and image-sets as linear subspaces has proven beneficial for many visual recognition tasks. However, it also incurs challenges arising from the fact that linear subspaces do not obey Euclidean geometry, but lie on a special type of Riemannian manifolds known as Grassmannian. To leverage the techniques developed for Euclidean spaces (e.g, support vector machines) with subspaces, several recent studies have proposed to embed the Grassmannian into a Hilbert space by making use of a positive definite kernel. Unfortunately, only two Grassmannian kernels are known, none of which -as we will show- is universal, which limits their ability to approximate a target function arbitrarily well. Here, we introduce several positive definite Grassmannian kernels, including universal ones, and demonstrate their superiority over previously-known kernels in various tasks, such as classification, clustering, sparse coding and hashing

Face Detection with Effective Feature Extraction

There is an abundant literature on face detection due to its important role in many vision applications. Since Viola and Jones proposed the first real-time AdaBoost based face detector, Haar-like features have been adopted as the method of choice for frontal face detection. In this work, we show that simple features other than Haar-like features can also be applied for training an effective face detector. Since, single feature is not discriminative enough to separate faces from difficult non-faces, we further improve the generalization performance of our simple features by introducing feature co-occurrences. We demonstrate that our proposed features yield a performance improvement compared to Haar-like features. In addition, our findings indicate that features play a crucial role in the ability of the system to generalize.Comment: 7 pages. Conference version published in Asian Conf. Comp. Vision 201

The Conditional Lucas & Kanade Algorithm

The Lucas & Kanade (LK) algorithm is the method of choice for efficient dense image and object alignment. The approach is efficient as it attempts to model the connection between appearance and geometric displacement through a linear relationship that assumes independence across pixel coordinates. A drawback of the approach, however, is its generative nature. Specifically, its performance is tightly coupled with how well the linear model can synthesize appearance from geometric displacement, even though the alignment task itself is associated with the inverse problem. In this paper, we present a new approach, referred to as the Conditional LK algorithm, which: (i) directly learns linear models that predict geometric displacement as a function of appearance, and (ii) employs a novel strategy for ensuring that the generative pixel independence assumption can still be taken advantage of. We demonstrate that our approach exhibits superior performance to classical generative forms of the LK algorithm. Furthermore, we demonstrate its comparable performance to state-of-the-art methods such as the Supervised Descent Method with substantially less training examples, as well as the unique ability to "swap" geometric warp functions without having to retrain from scratch. Finally, from a theoretical perspective, our approach hints at possible redundancies that exist in current state-of-the-art methods for alignment that could be leveraged in vision systems of the future.Comment: 17 pages, 11 figure

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

World Conference on Transport Research - WCTR 2016 Shanghai. 10-15 July 2016

This paper summarizes the key developments of carrier selection literature, especially from the view of survey research. Based on the literature review suggestions on how to make the analysis of carrier selection more rigorous are made. In addition to the most predominant determinants of carrier selection such as cost, reliability and service level, new constructs measuring the role of information sharing capabilities and environmental issues are introduced.The second objective of the paper is to empirically test the suggested improvements in methodology with survey data. Research constructs measuring the role of both the old and new determinants of carrier selection are formulated and tested. Further, the constructs of carrier selection are tested against set of variables classifying the firms such as firm size, industry and strategic orientation of the firm in order to see if the strategic orientation of the firm is influencing the carrier selection criteria. Methods of content analysis are used to sum up the previous literature in order to identify the key determinants of carrier selection that have previously been used. Based on the literature review, updated research constructs of carrier selection are formulated. Further, these constructs are tested with factor analysis in order to analyze the validity of the constructs.The empirical data employed in the analysis consists of a self-reported survey data of 483 manufacturing and trading firms operating in Finland. The survey data is analyzed by using descriptive statistics, correlation analysis and ANOVA in order to see whether the carrier selection criteria are dependent on the characteristics of the firm.The paper is expected to contribute on two separate levels. First, the paper introduces and empirically tests an improved survey methodology of how to analyse the carrier selection. As the survey methodology includes new constructs such as the role of information sharing and environmental questions, the empirical results presents evidence on what is their relative role compared to more traditional determinants of carrier selection. Further, the results provide empirical evidence on the effect of firm characteristics on the importance of carrier selection criteria. (C) 2017 The Authors. Published by Elsevier B.V