This paper presents a building material information system that helps construction manufacturers, architects and builders to manage building material information quickly and precisely throughout the life-cycle of a product. In the construction industry, it is getting more difficult to manage all the building resources for design and construction due to the rapid development of construction tech...

This paper describes various methods and approaches for language-based multimedia information retrieval, which have been developed in the projects POP-EYE and OLIVE and which will be developed further in the MUMIS project. All of these project aim at supporting automated indexing of video material by use of human language technologies. Thus, in contrast to image or sound-based retrieval methods...

We describe a Named Entity Recognition system for Dutch that combines gazetteers, handcrafted rules, and machine learning on the basis of seed material. We used gazetteers and a corpus to construct training material for Ripper, a rule learner. Instead of using Ripper to train a complete system, we used many different runs of Ripper in order to derive rules which we then interpreted and implemen...

In some climates, massive buildings made of stone, masonry, concrete, earth and … can be utilized as one of the simplest and most effective ways of reducing building heating and cooling loads. Very often such savings could be achieved in the design stage of the building and with a relatively low-cost. Such declines in building envelope heat losses combined with optimized material configurati...

Multi-scale gist (MS-gist) feature manifold for building recognition is presented in the paper. It is described as a two-stage model. In the first stage, we extract the multi-scale gist features that represent the structural information of the building images. Since the MS-gist features are extrinsically high dimensional and intrinsically low dimensional, in the second stage, an enhanced fuzzy ...

Today most mobile telephones come equipped with a camera. This gives rise to interesting new possibilities for applications of computer vision, such as building recognition software running locally on the mobile phone. Algorithms for building recognition need to be robust under noise, occlusion, varying lighting conditions and different points of view. We present such an algorithm using local i...

Lidar data has proved to be a promising data source for various mapping and 3D modeling of buildings. Nevertheless, traditional manually building extraction from Lidar data is highly labor-intensive, time-consuming and very expensive. During the past decade many researchers in photogrammetry, remote sensing and computer vision communities have been trying to study and develop the automatic or s...

Material recognition is an important subtask in computer vision. In this paper, we aim for the identification of material categories from a single image captured under unknown illumination and view conditions. Therefore, we use several features which cover various aspects of material appearance and perform supervised classification using Support Vector Machines. We demonstrate the feasibility o...

Material recognition is a fundamental problem in perception that is receiving increasing attention. Following the recent work using Flickr [16, 23], we empirically study material recognition of real-world objects using a rich set of local features. We use the Kernel Descriptor framework [5] and extend the set of descriptors to include materialmotivated attributes using variances of gradient ori...

how to deal with the prohibiting forbiddance in the context of trade is the difficult mystery of forbidden professions (makāsib muharrameh). some would consider it as an autumn breeze, impeding the thriving transactions of the market; others perceive the encounter of the forbidding prohibition with trade as a collision of two chemicals getting mixed with each other and producing a third materia...