877 resultados para 3D user interface


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With regard to the long-standing problem of the semantic gap between low-level image features and high-level human knowledge, the image retrieval community has recently shifted its emphasis from low-level features analysis to high-level image semantics extrac- tion. User studies reveal that users tend to seek information using high-level semantics. Therefore, image semantics extraction is of great importance to content-based image retrieval because it allows the users to freely express what images they want. Semantic content annotation is the basis for semantic content retrieval. The aim of image anno- tation is to automatically obtain keywords that can be used to represent the content of images. The major research challenges in image semantic annotation are: what is the basic unit of semantic representation? how can the semantic unit be linked to high-level image knowledge? how can the contextual information be stored and utilized for image annotation? In this thesis, the Semantic Web technology (i.e. ontology) is introduced to the image semantic annotation problem. Semantic Web, the next generation web, aims at mak- ing the content of whatever type of media not only understandable to humans but also to machines. Due to the large amounts of multimedia data prevalent on the Web, re- searchers and industries are beginning to pay more attention to the Multimedia Semantic Web. The Semantic Web technology provides a new opportunity for multimedia-based applications, but the research in this area is still in its infancy. Whether ontology can be used to improve image annotation and how to best use ontology in semantic repre- sentation and extraction is still a worth-while investigation. This thesis deals with the problem of image semantic annotation using ontology and machine learning techniques in four phases as below. 1) Salient object extraction. A salient object servers as the basic unit in image semantic extraction as it captures the common visual property of the objects. Image segmen- tation is often used as the �rst step for detecting salient objects, but most segmenta- tion algorithms often fail to generate meaningful regions due to over-segmentation and under-segmentation. We develop a new salient object detection algorithm by combining multiple homogeneity criteria in a region merging framework. 2) Ontology construction. Since real-world objects tend to exist in a context within their environment, contextual information has been increasingly used for improving object recognition. In the ontology construction phase, visual-contextual ontologies are built from a large set of fully segmented and annotated images. The ontologies are composed of several types of concepts (i.e. mid-level and high-level concepts), and domain contextual knowledge. The visual-contextual ontologies stand as a user-friendly interface between low-level features and high-level concepts. 3) Image objects annotation. In this phase, each object is labelled with a mid-level concept in ontologies. First, a set of candidate labels are obtained by training Support Vectors Machines with features extracted from salient objects. After that, contextual knowledge contained in ontologies is used to obtain the �nal labels by removing the ambiguity concepts. 4) Scene semantic annotation. The scene semantic extraction phase is to get the scene type by using both mid-level concepts and domain contextual knowledge in ontologies. Domain contextual knowledge is used to create scene con�guration that describes which objects co-exist with which scene type more frequently. The scene con�guration is represented in a probabilistic graph model, and probabilistic inference is employed to calculate the scene type given an annotated image. To evaluate the proposed methods, a series of experiments have been conducted in a large set of fully annotated outdoor scene images. These include a subset of the Corel database, a subset of the LabelMe dataset, the evaluation dataset of localized semantics in images, the spatial context evaluation dataset, and the segmented and annotated IAPR TC-12 benchmark.

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This paper introduces Sapporo World Window, a screen-based application that is currently under development for the new underway passage at the centre of Sapporo City. There are ten large public screens installed in the space, displaying user-generated videos about various aspects of the city and a real-time map that visualises users’ interaction with the city. The application aims to engage the general public by functioning as a unique ‘point of connection’ for socio-cultural and technological interactions, making the space a lively social place where people can have meaningful experiences of interacting with people and places of Sapporo through mobile phones (keitai) and the public screens in the space. This paper first outlines the contextual background and key concept for the application’s design. Then the paper discusses the user interaction processes, technical specifications, and interface design, followed by the conclusions and outlook.

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This paper reports on three primary school students’ explorations of 3D rotation in a virtual reality learning environment (VRLE) named VRMath. When asked to investigate if you would face the same direction when you turn right 45 degrees first then roll up 45 degrees, or when you roll up 45 degrees first then turn right 45 degrees, the students found that the different order of the two turns ended up with different directions in the VRLE. This was contrary to the students’ prior predictions based on using pen, paper and body movements. The findings of this study showed the difficulty young children have in perceiving and understanding the non-commutative nature of 3D rotation and the power of the computational VRLE in giving students experiences that they rarely have in real life with 3D manipulations and 3D mental movements.

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This chapter sets out the debates about the changing role of audiences in relation to user-created content as they appear in New Media and Cultural Studies. The discussion moves beyond the simple dichotomies between active producers and passive audiences, and draws on empirical evidence, in order to examine those practices that are most ordinary and widespread. Building on the knowledge of television’s role in facilitating public life, and the everyday, affective practices through which it is experienced and used, I focus on the way in which YouTube operates as a site of community, creativity and cultural citizenship; and as an archive of popular cultural memory.

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3D in vitro model systems that are able to mimic the in vivo microenvironment are now highly sought after in cancer research. Antheraea mylitta silk fibroin protein matrices were investigated as potential biomaterial for in vitro tumor modeling. We compared the characteristics of MDA-MB-231 cells on A. mylitta, Bombyx mori silk matrices, Matrigel, and tissue culture plates. The attachment and morphology of the MDA-MB-231 cell line on A. mylitta silk matrices was found to be better than on B. mori matrices and comparable to Matrigel and tissue culture plates. The cells grown in all 3D cultures showed more MMP-9 activity, indicating a more invasive potential. In comparison to B. mori fibroin, A. mylitta fibroin not only provided better cell adhesion, but also improved cell viability and proliferation. Yield coefficient of glucose consumed to lactate produced by cells on 3D A. mylitta fibroin was found to be similar to that of cancer cells in vivo. LNCaP prostate cancer cells were also cultured on 3D A. mylitta fibroin and they grew as clumps in long term culture. The results indicate that A. mylitta fibroin scaffold can provide an easily manipulated microenvironment system to investigate individual factors such as growth factors and signaling peptides, as well as evaluation of anticancer drugs.

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Process models are used by information professionals to convey semantics about the business operations in a real world domain intended to be supported by an information system. The understandability of these models is vital to them being used for information systems development. In this paper, we examine two factors that we predict will influence the understanding of a business process that novice developers obtain from a corresponding process model: the content presentation form chosen to articulate the business domain, and the user characteristics of the novice developers working with the model. Our experimental study provides evidence that novice developers obtain similar levels of understanding when confronted with an unfamiliar or a familiar process model. However, previous modeling experience, the use of English as a second language, and previous work experience in BPM are important influencing factors of model understanding. Our findings suggest that education and research in process modeling should increase the focus on human factors and how they relate to content and content presentation formats for different modeling tasks. We discuss implications for practice and research.

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“What did you think you were doing?” Was the question posed by the conference organizers to me as the inventor and constructor of the first working Tangible Interfaces over 40 years ago. I think the question was intended to encourage me to talk about the underlying ideas and intentionality rather than describe an endless sequence of electronic bricks and that is what I shall do in this presentation. In the sixties the prevalent idea for a graphics interface was an analogue with sketching which was to somehow be understood by the computer as three dimensional form. I rebelled against this notion for reasons which I will explain in the presentation and instead came up with tangible physical three dimensional intelligent objects. I called these first prototypes “Intelligent Physical Modelling Systems” which is a really dumb name for an obvious concept. I am eternally grateful to Hiroshi Ishii for coining the term “Tangible User Interfaces” - the same idea but with a much smarter name. Another motivator was user involvement in the design process, and that led to the Generator (1979) project with Cedric Price for the world’s first intelligent building capable of organizing itself in response to the appetites of the users. The working model of that project is in MoMA. And the same motivation led to a self builders design kit (1980) for Walter Segal which facilitated self-builders to design their own houses. And indeed as the organizer’s question implied, the motivation and intentionality of these projects developed over the years in step with advancing technology. The speaker will attempt to articulate these changes with medical, psychological and educational examples. Much of this later work indeed stemming from the Media Lab where we are talking. Related topics such as “tangible thinking” and “intelligent teacups” will be introduced and the presentation will end with some speculations for the future. The presentation will be given against a background of images of early prototypes many of which have never been previously published.

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We have used a scanning tunneling microscope to manipulate heteroleptic phthalocyaninato, naphthalocyaninato, porphyrinato double-decker molecules at the liquid/solid interface between 1-phenyloctane solvent and graphite. We employed nano-grafting of phthalocyanines with eight octyl chains to place these molecules into a matrix of heteroleptic double-decker molecules; the overlayer structure is epitaxial on graphite. We have also used nano-grafting to place double-decker molecules in matrices of single-layer phthalocyanines with octyl chains. Rectangular scans with a scanning tunneling microscope at low bias voltage resulted in the removal of the adsorbed doubledecker molecular layer and substituted the double-decker molecules with bilayer-stacked phthalocyanines from phenyloctane solution. Single heteroleptic double-decker molecules with lutetium sandwiched between naphthalocyanine and octaethylporphyrin were decomposed with voltage pulses from the probe tip; the top octaethylporphyrin ligand was removed and the bottom naphthalocyanine ligand remained on the surface. A domain of decomposed molecules was formed within the double-decker molecular domain, and the boundary of the decomposed molecular domain self-cured to become rectangular. We demonstrated a molecular “sliding block puzzle” with cascades of double-decker molecules on the graphite surface.

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The paper provides an assessment of the performance of commercial Real Time Kinematic (RTK) systems over longer than recommended inter-station distances. The experiments were set up to test and analyse solutions from the i-MAX, MAX and VRS systems being operated with three triangle shaped network cells, each having an average inter-station distance of 69km, 118km and 166km. The performance characteristics appraised included initialization success rate, initialization time, RTK position accuracy and availability, ambiguity resolution risk and RTK integrity risk in order to provide a wider perspective of the performance of the testing systems. ----- ----- The results showed that the performances of all network RTK solutions assessed were affected by the increase in the inter-station distances to similar degrees. The MAX solution achieved the highest initialization success rate of 96.6% on average, albeit with a longer initialisation time. Two VRS approaches achieved lower initialization success rate of 80% over the large triangle. In terms of RTK positioning accuracy after successful initialisation, the results indicated a good agreement between the actual error growth in both horizontal and vertical components and the accuracy specified in the RMS and part per million (ppm) values by the manufacturers. ----- ----- Additionally, the VRS approaches performed better than the MAX and i-MAX when being tested under the standard triangle network with a mean inter-station distance of 69km. However as the inter-station distance increases, the network RTK software may fail to generate VRS correction and then may turn to operate in the nearest single-base RTK (or RAW) mode. The position uncertainty reached beyond 2 meters occasionally, showing that the RTK rover software was using an incorrect ambiguity fixed solution to estimate the rover position rather than automatically dropping back to using an ambiguity float solution. Results identified that the risk of incorrectly resolving ambiguities reached 18%, 20%, 13% and 25% for i-MAX, MAX, Leica VRS and Trimble VRS respectively when operating over the large triangle network. Additionally, the Coordinate Quality indicator values given by the Leica GX1230 GG rover receiver tended to be over-optimistic and not functioning well with the identification of incorrectly fixed integer ambiguity solutions. In summary, this independent assessment has identified some problems and failures that can occur in all of the systems tested, especially when being pushed beyond the recommended limits. While such failures are expected, they can offer useful insights into where users should be wary and how manufacturers might improve their products. The results also demonstrate that integrity monitoring of RTK solutions is indeed necessary for precision applications, thus deserving serious attention from researchers and system providers.

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Personalised social matching systems can be seen as recommender systems that recommend people to others in the social networks. However, with the rapid growth of users in social networks and the information that a social matching system requires about the users, recommender system techniques have become insufficiently adept at matching users in social networks. This paper presents a hybrid social matching system that takes advantage of both collaborative and content-based concepts of recommendation. The clustering technique is used to reduce the number of users that the matching system needs to consider and to overcome other problems from which social matching systems suffer, such as cold start problem due to the absence of implicit information about a new user. The proposed system has been evaluated on a dataset obtained from an online dating website. Empirical analysis shows that accuracy of the matching process is increased, using both user information (explicit data) and user behavior (implicit data).

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This paper attempts to develop a theoretical acceptance model for measuring Web personalization success. Key factors impacting Web personalization acceptance are identified from a detailed literature review. The final model is then cast in a structural equation modeling (SEM) framework comprising nineteen manifest variables, which are grouped into three focal behaviors of Web users. These variables could provide a framework for better understanding of numerous factors that contribute to the success measures of Web personalization technology. Especially, those concerning the quality of personalized features and how personalized information through personalized Website can be delivered to the user. The interrelationship between success constructs is also explained. Empirical validations of this theoretical model are expected on future research.

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Detection of Region of Interest (ROI) in a video leads to more efficient utilization of bandwidth. This is because any ROIs in a given frame can be encoded in higher quality than the rest of that frame, with little or no degradation of quality from the perception of the viewers. Consequently, it is not necessary to uniformly encode the whole video in high quality. One approach to determine ROIs is to use saliency detectors to locate salient regions. This paper proposes a methodology for obtaining ground truth saliency maps to measure the effectiveness of ROI detection by considering the role of user experience during the labelling process of such maps. User perceptions can be captured and incorporated into the definition of salience in a particular video, taking advantage of human visual recall within a given context. Experiments with two state-of-the-art saliency detectors validate the effectiveness of this approach to validating visual saliency in video. This paper will provide the relevant datasets associated with the experiments.

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Eigen-based techniques and other monolithic approaches to face recognition have long been a cornerstone in the face recognition community due to the high dimensionality of face images. Eigen-face techniques provide minimal reconstruction error and limit high-frequency content while linear discriminant-based techniques (fisher-faces) allow the construction of subspaces which preserve discriminatory information. This paper presents a frequency decomposition approach for improved face recognition performance utilising three well-known techniques: Wavelets; Gabor / Log-Gabor; and the Discrete Cosine Transform. Experimentation illustrates that frequency domain partitioning prior to dimensionality reduction increases the information available for classification and greatly increases face recognition performance for both eigen-face and fisher-face approaches.

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The self-assembling behavior and microscopic structure of zinc oxide nanoparticle Langmuir-Blodgett monolayer films were investigated for the case of zinc oxide nanoparticles coated with a hydrophobic layer of dodecanethiol. Evolution of nanoparticle film structure as a function of surface pressure (π) at the air-water interface was monitored in situ using Brewster’s angle microscopy, where it was determined that π=16 mN/m produced near-defect-free monolayer films. Transmission electron micrographs of drop-cast and Langmuir-Schaefer deposited films of the dodecanethiol-coated zinc oxide nanoparticles revealed that the nanoparticle preparation method yielded a microscopic structure that consisted of one-dimensional rodlike assemblies of nanoparticles with typical dimensions of 25 x 400 nm, encased in the organic dodecanethiol layer. These nanoparticle-containing rodlike micelles were aligned into ordered arrangements of parallel rods using the Langmuir-Blodgett technique.

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The field of literacy studies has always been challenged by the changing technologies that humans have used to express, represent and communicate their feelings, ideas, understandings and knowledge. However, while the written word has remained central to literacy processes over a long period, it is generally accepted that there have been significant changes to what constitutes ‘literate’ practice. In particular, the status of the printed word has been challenged by the increasing dominance of the image, along with the multimodal meaning-making systems facilitated by digital media. For example, Gunther Kress and other members of the New London Group have argued that the second half of the twentieth century saw a significant cultural shift from the linguistic to the visual as the dominant semiotic mode. This in turn, they suggest, was accompanied by a cultural shift ‘from page to screen’ as a dominant space of representation (e.g. Cope & Kalantzis, 2000; Kress, 2003; New London Group, 1996). In a similar vein, Bill Green has noted that we have witnessed a shift from the regime of the print apparatus to a regime of the digital electronic apparatus (Lankshear, Snyder and Green, 2000). For these reasons, the field of literacy education has been challenged to find new ways to conceptualise what is meant by ‘literacy’ in the twenty first century and to rethink the conditions under which children might best be taught to be fully literate so that they can operate with agency in today’s world.