20,186 research outputs found

    Fireground location understanding by semantic linking of visual objects and building information models

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    This paper presents an outline for improved localization and situational awareness in fire emergency situations based on semantic technology and computer vision techniques. The novelty of our methodology lies in the semantic linking of video object recognition results from visual and thermal cameras with Building Information Models (BIM). The current limitations and possibilities of certain building information streams in the context of fire safety or fire incident management are addressed in this paper. Furthermore, our data management tools match higher-level semantic metadata descriptors of BIM and deep-learning based visual object recognition and classification networks. Based on these matches, estimations can be generated of camera, objects and event positions in the BIM model, transforming it from a static source of information into a rich, dynamic data provider. Previous work has already investigated the possibilities to link BIM and low-cost point sensors for fireground understanding, but these approaches did not take into account the benefits of video analysis and recent developments in semantics and feature learning research. Finally, the strengths of the proposed approach compared to the state-of-the-art is its (semi -)automatic workflow, generic and modular setup and multi-modal strategy, which allows to automatically create situational awareness, to improve localization and to facilitate the overall fire understanding

    A phenomenological approach to multisource data integration: Analysing infrared and visible data

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    A new method is described for combining multisensory data for remote sensing applications. The approach uses phenomenological models which allow the specification of discriminatory features that are based on intrinsic physical properties of imaged surfaces. Thermal and visual images of scenes are analyzed to estimate surface heat fluxes. Such analysis makes available a discriminatory feature that is closely related to the thermal capacitance of the imaged objects. This feature provides a method for labelling image regions based on physical properties of imaged objects. This approach is different from existing approaches which use the signal intensities in each channel (or an arbitrary linear or nonlinear combination of signal intensities) as features - which are then classified by a statistical or evident approach

    Cloud cover typing from environmental satellite imagery. Discriminating cloud structure with Fast Fourier Transforms (FFT)

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    The use of two dimensional Fast Fourier Transforms (FFTs) subjected to pattern recognition technology for the identification and classification of low altitude stratus cloud structure from Geostationary Operational Environmental Satellite (GOES) imagery was examined. The development of a scene independent pattern recognition methodology, unconstrained by conventional cloud morphological classifications was emphasized. A technique for extracting cloud shape, direction, and size attributes from GOES visual imagery was developed. These attributes were combined with two statistical attributes (cloud mean brightness, cloud standard deviation), and interrogated using unsupervised clustering amd maximum likelihood classification techniques. Results indicate that: (1) the key cloud discrimination attributes are mean brightness, direction, shape, and minimum size; (2) cloud structure can be differentiated at given pixel scales; (3) cloud type may be identifiable at coarser scales; (4) there are positive indications of scene independence which would permit development of a cloud signature bank; (5) edge enhancement of GOES imagery does not appreciably improve cloud classification over the use of raw data; and (6) the GOES imagery must be apodized before generation of FFTs

    Human emotional response to energy visualisations

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    This is the post-print version of the final paper published in International Journal of Industrial Ergonomics. The published article is available from the link below. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. Copyright @ 2012 Elsevier B.V.Past research has found that frequent energy usage feedback is an important factor in reducing home energy consumption, and that the sensory appeal and cognitive relevance of the feedback are key components of user engagement with energy systems. The visual design of the information interface is important not just due to its role in communicating data of cognitive relevance, but also because the choice of information type and format is important towards achieving interactive Hebbian learning. The objective of the current research study was to investigate the possible effect of image format on the human emotional response to scenes of energy systems, and to evaluate whether any gender related differences in emotional response occurred. An automated PC-based test was developed which utilised five visual image formats (Optical Gray-Scale, Optical Coloured, Optical Augmented, Infrared Gray-Scale and Infrared Blue-Red) and nine home energy scenes (hot water boiler, radiator, water faucet, kitchen oven, tea kettle, toaster, electrical connector, laptop computer and tea mug). The emotional response of the participant was measured in the automated test by means of a Self-Assessment Manikin (SAM) which provided symbolic graphical representations of the human body under various degrees of emotional response, and associated Likert format rating scales for the valence and activation level of the emotional response. Comparison of the results obtained for the different visual scenes suggests that the greatest level of human emotional activation was achieved by the Infrared Blue-Red (thermal image) format, and that, generally, coloured images provided higher levels of emotional activation than gray-scale images. The increased activation achieved by the infrared images suggests attention capturing potential due to novelty, or due to the direct link to heat and energy, or both. Significant differences in emotional response (both activation and valence) were found to occur as a function of gender. The current results provide first guidance which a designer can use when choosing image spectrum and colours to represent energy systems on the displays of thermostats, smart meters and the energy devices. Relevance to industry - The current results provide first guidance which a designer can use when choosing image spectrum and colours to represent energy systems on the displays of thermostats, smart meters and the energy devices. Such design guidance is currently lacking internationally but is of increasing importance due to the expansion of digital devices, internet services and the upcoming internet-of-things

    Site Characterization Using Integrated Imaging Analysis Methods on Satellite Data of the Islamabad, Pakistan, Region

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    We develop an integrated digital imaging analysis approach to produce a first-approximation site characterization map for Islamabad, Pakistan, based on remote-sensing data. We apply both pixel-based and object-oriented digital imaging analysis methods to characterize detailed (1:50,000) geomorphology and geology from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) satellite imagery. We use stereo-correlated relative digital elevation models (rDEMs) derived from ASTER data, as well as spectra in the visible near-infrared (VNIR) to thermal infrared (TIR) domains. The resulting geomorphic units in the study area are classified as mountain (including the Margala Hills and the Khairi Murat Ridge), piedmont, and basin terrain units. The local geologic units are classified as limestone in the Margala Hills and the Khairi Murat Ridge and sandstone rock types for the piedmonts and basins. Shear-wave velocities for these units are assigned in ranges based on established correlations in California. These ranges include Vs30-values to be greater than 500 m/sec for mountain units, 200–600 m/sec for piedmont units, and less than 300 m/sec for basin units. While the resulting map provides the basis for incorporating site response in an assessment of seismic hazard for Islamabad, it also demonstrates the potential use of remote-sensing data for site characterization in regions where only limited conventional mapping has been done

    Remote sensing of coastal wetland vegetation and estuarine water properties

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    There are no author-identified significant results in this report

    Earth observations from space: Outlook for the geological sciences

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    Remote sensing from space platforms is discussed as another tool available to geologists. The results of Nimbus observations, the ERTS program, and Skylab EREP are reviewed, and a multidisciplinary approach is recommended for meeting the challenges of remote sensing
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