11 resultados para Augmented reality systems

em Universidad de Alicante


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Early education is a key element for the future success of students in the education system. This work analyzes the feasibility of using augmented reality contents with preschool students (four and five years old) as a tool for improving their learning process. A quasi experimental design based on a nonequivalent groups posttest-only design was used. A didactic unit has been developed around the topic “animals” by the participant teachers. The control group followed all the didactic activities defined in the developed didactic materials, while the experimental group was provided in addition with some augmented reality contents. Results show improved learning outcomes in the experimental group with respect to the control group.

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Impure systems contain Objects and Subjects: Subjects are human beings. We can distinguish a person as an observer (subjectively outside the system) and that by definition is the Subject himself, and part of the system. In this case he acquires the category of object. Objects (relative beings) are significances, which are the consequence of perceptual beliefs on the part of the Subject about material or energetic objects (absolute beings) with certain characteristics.The IS (Impure System) approach is as follows: Objects are perceptual significances (relative beings) of material or energetic objects (absolute beings). The set of these objects will form an impure set of the first order. The existing relations between these relative objects will be of two classes: transactions of matter and/or energy and inferential relations. Transactions can have alethic modality: necessity, possibility, impossibility and contingency. Ontic existence of possibility entails that inferential relations have Deontic modality: obligation, permission, prohibition, faculty and analogy. We distinguished between theorems (natural laws) and norms (ethical, legislative and customary rules of conduct).

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The use of 3D imaging techniques has been early adopted in the footwear industry. In particular, 3D imaging could be used to aid commerce and improve the quality and sales of shoes. Footwear customization is an added value aimed not only to improve product quality, but also consumer comfort. Moreover, customisation implies a new business model that avoids the competition of mass production coming from new manufacturers settled mainly in Asian countries. However, footwear customisation implies a significant effort at different levels. In manufacturing, rapid and virtual prototyping is required; indeed the prototype is intended to become the final product. The whole design procedure must be validated using exclusively virtual techniques to ensure the feasibility of this process, since physical prototypes should be avoided. With regard to commerce, it would be desirable for the consumer to choose any model of shoes from a large 3D database and be able to try them on looking at a magic mirror. This would probably reduce costs and increase sales, since shops would not require storing every shoe model and the process of trying several models on would be easier and faster for the consumer. In this paper, new advances in 3D techniques coming from experience in cinema, TV and games are successfully applied to footwear. Firstly, the characteristics of a high-quality stereoscopic vision system for footwear are presented. Secondly, a system for the interaction with virtual footwear models based on 3D gloves is detailed. Finally, an augmented reality system (magic mirror) is presented, which is implemented with low-cost computational elements that allow a hypothetical customer to check in real time the goodness of a given virtual footwear model from an aesthetical point of view.

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This paper presents the use of immersive virtual reality systems in the educational intervention with Asperger students. The starting points of this study are features of these students' cognitive style that requires an explicit teaching style supported by visual aids and highly structured environments. The proposed immersive virtual reality system, not only to assess the student's behavior and progress, but also is able to adapt itself to the student's specific needs. Additionally, the immersive reality system is equipped with sensors that can determine certain behaviors of the students. This paper determines the possible inclusion of immersive virtual reality as a support tool and learning strategy in these particular students' intervention. With this objective two task protocols have been defined with which the behavior and interaction situations performed by participant students are recorded. The conclusions from this study talks in favor of the inclusion of these virtual immersive environments as a support tool in the educational intervention of Asperger syndrome students as their social competences and executive functions have improved.

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Nowadays, new computers generation provides a high performance that enables to build computationally expensive computer vision applications applied to mobile robotics. Building a map of the environment is a common task of a robot and is an essential part to allow the robots to move through these environments. Traditionally, mobile robots used a combination of several sensors from different technologies. Lasers, sonars and contact sensors have been typically used in any mobile robotic architecture, however color cameras are an important sensor due to we want the robots to use the same information that humans to sense and move through the different environments. Color cameras are cheap and flexible but a lot of work need to be done to give robots enough visual understanding of the scenes. Computer vision algorithms are computational complex problems but nowadays robots have access to different and powerful architectures that can be used for mobile robotics purposes. The advent of low-cost RGB-D sensors like Microsoft Kinect which provide 3D colored point clouds at high frame rates made the computer vision even more relevant in the mobile robotics field. The combination of visual and 3D data allows the systems to use both computer vision and 3D processing and therefore to be aware of more details of the surrounding environment. The research described in this thesis was motivated by the need of scene mapping. Being aware of the surrounding environment is a key feature in many mobile robotics applications from simple robotic navigation to complex surveillance applications. In addition, the acquisition of a 3D model of the scenes is useful in many areas as video games scene modeling where well-known places are reconstructed and added to game systems or advertising where once you get the 3D model of one room the system can add furniture pieces using augmented reality techniques. In this thesis we perform an experimental study of the state-of-the-art registration methods to find which one fits better to our scene mapping purposes. Different methods are tested and analyzed on different scene distributions of visual and geometry appearance. In addition, this thesis proposes two methods for 3d data compression and representation of 3D maps. Our 3D representation proposal is based on the use of Growing Neural Gas (GNG) method. This Self-Organizing Maps (SOMs) has been successfully used for clustering, pattern recognition and topology representation of various kind of data. Until now, Self-Organizing Maps have been primarily computed offline and their application in 3D data has mainly focused on free noise models without considering time constraints. Self-organising neural models have the ability to provide a good representation of the input space. In particular, the Growing Neural Gas (GNG) is a suitable model because of its flexibility, rapid adaptation and excellent quality of representation. However, this type of learning is time consuming, specially for high-dimensional input data. Since real applications often work under time constraints, it is necessary to adapt the learning process in order to complete it in a predefined time. This thesis proposes a hardware implementation leveraging the computing power of modern GPUs which takes advantage of a new paradigm coined as General-Purpose Computing on Graphics Processing Units (GPGPU). Our proposed geometrical 3D compression method seeks to reduce the 3D information using plane detection as basic structure to compress the data. This is due to our target environments are man-made and therefore there are a lot of points that belong to a plane surface. Our proposed method is able to get good compression results in those man-made scenarios. The detected and compressed planes can be also used in other applications as surface reconstruction or plane-based registration algorithms. Finally, we have also demonstrated the goodness of the GPU technologies getting a high performance implementation of a CAD/CAM common technique called Virtual Digitizing.

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In this work, we propose the use of the neural gas (NG), a neural network that uses an unsupervised Competitive Hebbian Learning (CHL) rule, to develop a reverse engineering process. This is a simple and accurate method to reconstruct objects from point clouds obtained from multiple overlapping views using low-cost sensors. In contrast to other methods that may need several stages that include downsampling, noise filtering and many other tasks, the NG automatically obtains the 3D model of the scanned objects. To demonstrate the validity of our proposal we tested our method with several models and performed a study of the neural network parameterization computing the quality of representation and also comparing results with other neural methods like growing neural gas and Kohonen maps or classical methods like Voxel Grid. We also reconstructed models acquired by low cost sensors that can be used in virtual and augmented reality environments for redesign or manipulation purposes. Since the NG algorithm has a strong computational cost we propose its acceleration. We have redesigned and implemented the NG learning algorithm to fit it onto Graphics Processing Units using CUDA. A speed-up of 180× faster is obtained compared to the sequential CPU version.

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Building Information Modelling (BIM) provides a shared source of information about a built asset, which creates a collaborative virtual environment for project teams. Literature suggests that to collaborate efficiently, the relationship between the project team is based on sympathy, obligation, trust and rapport. Communication increases in importance when working collaboratively but effective communication can only be achieved when the stakeholders are willing to act, react, listen and share information. Case study research and interviews with Architecture, Engineering and Construction (AEC) industry experts suggest that synchronous face-to-face communication is project teams’ preferred method, allowing teams to socialise and build rapport, accelerating the creation of trust between the stakeholders. However, virtual unified communication platforms are a close second-preferred option for communication between the teams. Effective methods for virtual communication in professional practice, such as virtual collaboration environments (CVE), that build trust and achieve similar spontaneous responses as face-to-face communication, are necessary to face the global challenges and can be achieved with the right people, processes and technology. This research paper investigates current industry methods for virtual communication within BIM projects and explores the suitability of avatar interaction in a collaborative virtual environment as an alternative to face-to-face communication to enhance collaboration between design teams’ professional practice on a project. Hence, this paper presents comparisons between the effectiveness of these communication methods within construction design teams with results of further experiments conducted to test recommendations for more efficient methods for virtual communication to add value in the workplace between design teams.

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Linguistic systems are the human tools to understand reality. But is it possible to attain this reality? The reality that we perceive, is it just a fragmented reality of which we are part? In this paper the authors present is an attempt to address this question from an epistemological and philosophic linguistic point of view.

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Science has been developed from the rational-empirical methods, having as a consequence, the representation of existing phenomena without understanding the root causes. The question which currently has is the sense of the being, and in a simplified way, one can say that the dogmatic religion lead to misinterpretations, the empirical sciences contain the exact rational representations of phenomena. Thus, Science has been able to get rid of the dogmatic religion. The project for the sciences of being looks to return to reality its essential foundations; under the plan of theory of systems necessarily involves a search for the meaning of Reality.

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In this paper, the authors extend and generalize the methodology based on the dynamics of systems with the use of differential equations as equations of state, allowing that first order transformed functions not only apply to the primitive or original variables, but also doing so to more complex expressions derived from them, and extending the rules that determine the generation of transformed superior to zero order (variable or primitive). Also, it is demonstrated that for all models of complex reality, there exists a complex model from the syntactic and semantic point of view. The theory is exemplified with a concrete model: MARIOLA model.

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Ideologies face two critical problems in the reality, the problem of commitment and the problem of validation. Commitment and validation are two separate phenomena, in spite of the near universal myth that the human is committed because his beliefs are valid. Ideologies not only seem external and valid but also worth whatever discomforts believing entails. In this paper the authors develop a theory of social commitment and social validation using concepts of validation of neutrosophic logic.