-In this paper we present the overall study that includes the model developed (VS Model) and the experiences performed, with an automatic bidirectional sign language translator, between written and sign language, which is being supervised by the research group GILT (Graphics, interaction & learning technologies) under the frame of a national project called Virtual Sign (VS project). This project aims to develop and evaluate a model that facilitates access for the deaf and hearing impaired to digital content -in particular the educational content and learning objects -creating the conditions for greater social inclusion of deaf and hearing impaired people. Access to digital content will be supported by an automatic translator between Portuguese Writing (LEP) and Portuguese Sign Language (LGP) supported by an interaction model.
In this work we explore multiprocessor computer architectures to propose an effective method for solving the Simultaneous Localization and Mapping Problem. The proposed method makes use of multithreading to parallelize a Rao-Blackwellized Particle Filter approach. By applying the method in common computers found in robots, it is shown that a significant gain in efficiency can be obtained. Furthermore, the parallel method enables us to raise the number of particles up to values that would not be possible in a single threaded solution, thus gaining in localization precision and map accuracy. In order to analyze SLAM results, frequently used datasets by the robotics community were used, and a benchmarking metric was applied.
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