972 resultados para Depth from focus


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The ongoing growth of the World Wide Web, catalyzed by the increasing possibility of ubiquitous access via a variety of devices, continues to strengthen its role as our prevalent information and commmunication medium. However, although tools like search engines facilitate retrieval, the task of finally making sense of Web content is still often left to human interpretation. The vision of supporting both humans and machines in such knowledge-based activities led to the development of different systems which allow to structure Web resources by metadata annotations. Interestingly, two major approaches which gained a considerable amount of attention are addressing the problem from nearly opposite directions: On the one hand, the idea of the Semantic Web suggests to formalize the knowledge within a particular domain by means of the "top-down" approach of defining ontologies. On the other hand, Social Annotation Systems as part of the so-called Web 2.0 movement implement a "bottom-up" style of categorization using arbitrary keywords. Experience as well as research in the characteristics of both systems has shown that their strengths and weaknesses seem to be inverse: While Social Annotation suffers from problems like, e. g., ambiguity or lack or precision, ontologies were especially designed to eliminate those. On the contrary, the latter suffer from a knowledge acquisition bottleneck, which is successfully overcome by the large user populations of Social Annotation Systems. Instead of being regarded as competing paradigms, the obvious potential synergies from a combination of both motivated approaches to "bridge the gap" between them. These were fostered by the evidence of emergent semantics, i. e., the self-organized evolution of implicit conceptual structures, within Social Annotation data. While several techniques to exploit the emergent patterns were proposed, a systematic analysis - especially regarding paradigms from the field of ontology learning - is still largely missing. This also includes a deeper understanding of the circumstances which affect the evolution processes. This work aims to address this gap by providing an in-depth study of methods and influencing factors to capture emergent semantics from Social Annotation Systems. We focus hereby on the acquisition of lexical semantics from the underlying networks of keywords, users and resources. Structured along different ontology learning tasks, we use a methodology of semantic grounding to characterize and evaluate the semantic relations captured by different methods. In all cases, our studies are based on datasets from several Social Annotation Systems. Specifically, we first analyze semantic relatedness among keywords, and identify measures which detect different notions of relatedness. These constitute the input of concept learning algorithms, which focus then on the discovery of synonymous and ambiguous keywords. Hereby, we assess the usefulness of various clustering techniques. As a prerequisite to induce hierarchical relationships, our next step is to study measures which quantify the level of generality of a particular keyword. We find that comparatively simple measures can approximate the generality information encoded in reference taxonomies. These insights are used to inform the final task, namely the creation of concept hierarchies. For this purpose, generality-based algorithms exhibit advantages compared to clustering approaches. In order to complement the identification of suitable methods to capture semantic structures, we analyze as a next step several factors which influence their emergence. Empirical evidence is provided that the amount of available data plays a crucial role for determining keyword meanings. From a different perspective, we examine pragmatic aspects by considering different annotation patterns among users. Based on a broad distinction between "categorizers" and "describers", we find that the latter produce more accurate results. This suggests a causal link between pragmatic and semantic aspects of keyword annotation. As a special kind of usage pattern, we then have a look at system abuse and spam. While observing a mixed picture, we suggest that an individual decision should be taken instead of disregarding spammers as a matter of principle. Finally, we discuss a set of applications which operationalize the results of our studies for enhancing both Social Annotation and semantic systems. These comprise on the one hand tools which foster the emergence of semantics, and on the one hand applications which exploit the socially induced relations to improve, e. g., searching, browsing, or user profiling facilities. In summary, the contributions of this work highlight viable methods and crucial aspects for designing enhanced knowledge-based services of a Social Semantic Web.

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In the absence of cues for absolute depth measurements as binocular disparity, motion, or defocus, the absolute distance between the observer and a scene cannot be measured. The interpretation of shading, edges and junctions may provide a 3D model of the scene but it will not inform about the actual "size" of the space. One possible source of information for absolute depth estimation is the image size of known objects. However, this is computationally complex due to the difficulty of the object recognition process. Here we propose a source of information for absolute depth estimation that does not rely on specific objects: we introduce a procedure for absolute depth estimation based on the recognition of the whole scene. The shape of the space of the scene and the structures present in the scene are strongly related to the scale of observation. We demonstrate that, by recognizing the properties of the structures present in the image, we can infer the scale of the scene, and therefore its absolute mean depth. We illustrate the interest in computing the mean depth of the scene with application to scene recognition and object detection.

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Omnidirectional cameras offer a much wider field of view than the perspective ones and alleviate the problems due to occlusions. However, both types of cameras suffer from the lack of depth perception. A practical method for obtaining depth in computer vision is to project a known structured light pattern on the scene avoiding the problems and costs involved by stereo vision. This paper is focused on the idea of combining omnidirectional vision and structured light with the aim to provide 3D information about the scene. The resulting sensor is formed by a single catadioptric camera and an omnidirectional light projector. It is also discussed how this sensor can be used in robot navigation applications

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Cloud optical depth is one of the most poorly observed climate variables. The new “cloud mode” capability in the Aerosol Robotic Network (AERONET) will inexpensively yet dramatically increase cloud optical depth observations in both number and accuracy. Cloud mode optical depth retrievals from AERONET were evaluated at the Atmospheric Radiation Measurement program’s Oklahoma site in sky conditions ranging from broken clouds to overcast. For overcast cases, the 1.5 min average AERONET cloud mode optical depths agreed to within 15% of those from a standard ground‐based flux method. For broken cloud cases, AERONET retrievals also captured rapid variations detected by the microwave radiometer. For 3 year climatology derived from all nonprecipitating clouds, AERONET monthly mean cloud optical depths are generally larger than cloud radar retrievals because of the current cloud mode observation strategy that is biased toward measurements of optically thick clouds. This study has demonstrated a new way to enhance the existing AERONET infrastructure to observe cloud optical properties on a global scale.

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Pulsed lidars are commonly used to retrieve vertical distributions of cloud and aerosol layers. It is widely believed that lidar cloud retrievals (other than cloud base altitude) are limited to optically thin clouds. Here, we demonstrate that lidars can retrieve optical depths of thick clouds using solar background light as a signal, rather than (as now) merely a noise to be subtracted. Validations against other instruments show that retrieved cloud optical depths agree within 10%–15% for overcast stratus and broken clouds. In fact, for broken cloud situations, one can retrieve not only the aerosol properties in clear-sky periods using lidar signals, but also the optical depth of thick clouds in cloudy periods using solar background signals. This indicates that, in general, it may be possible to retrieve both aerosol and cloud properties using a single lidar. Thus, lidar observations have great untapped potential to study interactions between clouds and aerosols.

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Ground-based aerosol optical depth (AOD) climatologies at three high-altitude sites in Switzerland (Jungfraujoch and Davos) and Southern Germany (Hohenpeissenberg) are updated and re-calibrated for the period 1995 – 2010. In addition, AOD time-series are augmented with previously unreported data, and are homogenized for the first time. Trend analysis revealed weak AOD trends (λ = 500 nm) at Jungfraujoch (JFJ; +0.007 decade-1), Davos (DAV; +0.002 decade-1) and Hohenpeissenberg (HPB; -0.011 decade-1) where the JFJ and HPB trends were statistically significant at the 95% and 90% confidence levels. However, a linear trend for the JFJ 1995 – 2005 period was found to be more appropriate than for 1995 – 2010 due to the influence of stratospheric AOD which gave a trend -0.003 decade-1 (significant at 95% level). When correcting for a recently available stratospheric AOD time-series, accounting for Pinatubo (1991) and more recent volcanic eruptions, the 1995 – 2010 AOD trends decreased slightly at DAV and HPB but remained weak at +0.000 decade-1 and -0.013 decade-1 (significant at 95% level). The JFJ 1995 – 2005 AOD time-series similarly decreased to -0.003 decade-1 (significant at 95% level). We conclude that despite a more detailed re40 analysis of these three time-series, which have been extended by five years to the end of 2010, a significant decrease in AOD at these three high-altitude sites has still not been observed.

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Leaders across companies initiate and implement change and thus are crucial for successful organizations. This study takes a competency perspective on leaders and investigates the competencies leaders show to facilitate effective change. The article explores the content of the construct of leaders’ change competency and examines its antecedents and effects. We conducted a case study in a German tourism company undergoing a major change process. The study identified (a) distinct content facets regarding the construct of leaders’ change competency along its two dimensions of leaders’ readiness for change and leaders’ change ability; (b) the construct’s antecedents, specifically contextual factors, leaders’ competency potentials, and attitudes toward change; and (c) beneficial effects of leaders’ change competency. The study ends with implications for research and leadership practice as well as suggestions for future studies on leaders’ change competency.

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Accurate co-ordination of accommodation and convergence is necessary to view near objects and develop fine motor co-ordination. We used a remote haploscopic videorefraction paradigm to measure longitudinal changes in simultaneous ocular accommodation and vergence to targets at different depths, and to all combinations of blur, binocular disparity, and change-in-size (“proximity”) cues. Infants were followed longitudinally and compared to older children and young adults, with the prediction that sensitivity to different cues would change during development. Mean infant responses to the most naturalistic condition were similar to those of adults from 6-7 weeks (accommodation) and 8-9 weeks (vergence). Proximity cues influenced responses most in infants less than 14 weeks of age, but sensitivity declined thereafter. Between 12-28 weeks of age infants were equally responsive to all three cues, while in older children and adults manipulation of disparity resulted in the greatest changes in response. Despite rapid development of visual acuity (thus increasing availability of blur cues), responses to blur were stable throughout development. Our results suggest that during much of infancy, vergence and accommodation responses are not dependent on the development of specific depth cues, but make use of any cues available to drive appropriate changes in response.

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This paper presents an analysis of ground-based Aerosol Optical Depth (AOD) observations by the Aerosol Robotic Network (AERONET) in South America from 2001 to 2007 in comparison with the satellite AOD product of Moderate Resolution Imaging Spectroradiometer (MODIS), aboard TERRA and AQUA satellites. Data of 12 observation sites were used with primary interest in AERONET sites located in or downwind of areas with high biomass burning activity and with measurements available for the full time range. Fires cause the predominant carbonaceous aerosol emission signal during the dry season in South America and are therefore a special focus of this study. Interannual and seasonal behavior of the observed AOD at different sites were investigated, showing clear differences between purely fire and urban influenced sites. An intercomparison of AERONET and MODIS AOD annual correlations revealed that neither an interannual long-term trend may be observed nor that correlations differ significantly owing to different overpass times of TERRA and AQUA. Individual anisotropic representativity areas for each AERONET site were derived by correlating daily AOD of each site for all years with available individual MODIS AOD pixels gridded to 1 degrees x 1 degrees. Results showed that for many sites a good AOD correlation (R(2) > 0.5) persists for large, often strongly anisotropic, areas. The climatological areas of common regional aerosol regimes often extend over several hundreds of kilometers, sometimes far across national boundaries. As a practical application, these strongly inhomogeneous and anisotropic areas of influence are being implemented in the tropospheric aerosol data assimilation system of the Coupled Chemistry-Aerosol-Tracer Transport Model coupled to the Brazilian Regional Atmospheric Modeling System (CCATT-BRAMS) at the Brazilian National Institute for Space Research (INPE). This new information promises an improved exploitation of local site sampling and, thus, chemical weather forecast.

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Dental markers have been used to unravel particularities of paleodiet, subsistence, social structure, and health. This article aims to compare oral pathology among four pre-Columbian groups with different degrees of agricultural and socio-cultural development but comparable ecological conditions who lived on the coastal desert of Peru. Three of these groups are assigned to distinct phases of the Formative Period (2500-1 BC), a time critical for our understanding of the development of agriculture and social complexity. The fourth group corresponds to the Late Intermediate Period (1000-1470 AD), when agriculture had its apogee and society was highly stratified. In this study we test whether there is an increase (1) in the frequency of carious lesions and (2) in caries depth, and (3) if there is a shift from occlusal to extra-occlusal caries locations with the development of agriculture. Therefore, we analyze the frequencies of carious lesions and antemortem tooth loss (AMTL), the caries distributions by age, sex, and type of tooth, as well as the tissues affected by, and the location of the carious lesions. Since there are no significant differences in the frequencies of carious lesions and AMTL between the groups, we reject hypothesis 1. In contrast, caries depth does increase, and caries location changes from occlusal to extra-occlusal sites with agricultural development. However, we can only corroborate hypothesis 2 and 3 when taking into consideration dental wear. Thus, we recommend that caries depth and locations should be used with evaluations of dental wear to reconstruct subsistence in ancient populations. Am J Phys Anthropol 143:75-91, 2010. (C) 2010 Wiley-Liss, Inc.