834 resultados para CAMERAS


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Research in the field of sports performance is constantly developing new technology to help extract meaningful data to aid in understanding in a multitude of areas such as improving technical or motor performance. Video playback has previously been extensively used for exploring anticipatory behaviour. However, when using such systems, perception is not active. This loses key information that only emerges from the dynamics of the action unfolding over time and the active perception of the observer. Virtual reality (VR) may be used to overcome such issues. This paper presents the architecture and initial implementation of a novel VR cricket simulator, utilising state of the art motion capture technology (21 Vicon cameras capturing kinematic profile of elite bowlers) and emerging VR technology (Intersense IS-900 tracking combined with Qualisys Motion capture cameras with visual display via Sony Head Mounted Display HMZ-T1), applied in a cricket scenario to examine varying components of decision and action for cricket batters. This provided an experience with a high level of presence allowing for a real-time egocentric view-point to be presented to participants. Cyclical user-testing was carried out, utilisng both qualitative and quantitative approaches, with users reporting a positive experience in use of the system.

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Este relatório apresenta o estudo de duas linhas de montagem de câmaras de vigilância da empresa Bosch Security Systems, S.A. de Ovar. Numa primeira fase procedeu-se à elaboração das listas de tarefas e respectivas precedências, seguindo-se a medição de trabalho, com o intuito de se actualizarem os tempos padrão existentes. Procedeu-se à comparação dos tempos obtidos com os que se encontravam em vigor de modo a perceber as diferenças e motivos das mesmas. Numa segunda fase, realizaram-se balanceamentos para as duas linhas tendo como cenários a manutenção das duas linhas e a possibilidade da sua junção numa linha única. Analisaram-se todos os resultados e efectuou-se um levantamento do investimento necessário associado a cada um dos cenários. Realizou-se deste modo uma análise de viabilidade com vista ao apoio à decisão. Por fim, realizou-se o workshop Lean Line Design que teve como resultado a configuração física da linha final. Este projecto permitiu chegar a resultados aliciantes, com ganhos a vários níveis. Constituiu mais uma acção de melhoria da empresa, levando-a a rectificar lacunas existentes e ao cumprimento de procedimentos ergonómicos que já se encontravam definidos.

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Ultrasonic, infrared, laser and other sensors are being applied in robotics. Although combinations of these have allowed robots to navigate, they are only suited for specific scenarios, depending on their limitations. Recent advances in computer vision are turning cameras into useful low-cost sensors that can operate in most types of environments. Cameras enable robots to detect obstacles, recognize objects, obtain visual odometry, detect and recognize people and gestures, among other possibilities. In this paper we present a completely biologically inspired vision system for robot navigation. It comprises stereo vision for obstacle detection, and object recognition for landmark-based navigation. We employ a novel keypoint descriptor which codes responses of cortical complex cells. We also present a biologically inspired saliency component, based on disparity and colour.

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Markerless systems are becoming more ubiquitous due to their increased use in video games consoles. Cheap cameras and software suites are making motion capture technologies more freely available to the digitally inclined choreographer. In this workshop we will demonstrate the opportunities and limitations provided by easily accessible and relatively inexpensive markerless motion capture systems. In particular we will explore the capacity of these systems to provide useful data in a live performance scenario where the latency, size and format of the captured data is crucial in allowing real-time processing and visualisation of the captured scene

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Thesis (Ph.D.)--University of Washington, 2015

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This Database was generated during the development of a computer vision-based system for safety purposes in nuclear plants. The system aims at detecting and tracking people within a nuclear plant. Further details may be found in the related thesis. The research was developed through a cooperation between the Graduate Electrical Engineering Program of Federal University of Rio de Janeiro (PEE/COPPE, UFRJ) and the Nuclear Engineering Institute of National Commission of Nuclear Energy (IEN, CNEN). The experimental part of this research was carried out in Argonauta, a nuclear research reactor belonging to IEN. The Database is made available in the sequel. All the videos are already rectified. The Projection and Homography matrices are given in the end, for both cameras. Please, acknowledge the use of this Database in any publication.

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Dissertação de Mestrado em Engenharia de Redes de Comunicação e Multimédia

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Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia de Redes de Comunicação e Multimédia

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Dissertação para a obtenção do grau de Mestre em Engenharia Electrotécnica Ramo de Energia

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Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia de redes de Comunicação e Multimédia

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Target tracking with bearing-only sensors is a challenging problem when the target moves dynamically in complex scenarios. Besides the partial observability of such sensors, they have limited field of views, occlusions can occur, etc. In those cases, cooperative approaches with multiple tracking robots are interesting, but the different sources of uncertain information need to be considered appropriately in order to achieve better estimates. Even though there exist probabilistic filters that can estimate the position of a target dealing with incertainties, bearing-only measurements bring usually additional problems with initialization and data association. In this paper, we propose a multi-robot triangulation method with a dynamic baseline that can triangulate bearing-only measurements in a probabilistic manner to produce 3D observations. This method is combined with a decentralized stochastic filter and used to tackle those initialization and data association issues. The approach is validated with simulations and field experiments where a team of aerial and ground robots with cameras track a dynamic target.

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In this paper we present a set of field tests for detection of human in the water with an unmanned surface vehicle using infrared and color cameras. These experiments aimed to contribute in the development of victim target tracking and obstacle avoidance for unmanned surface vehicles operating in marine search and rescue missions. This research is integrated in the work conducted in the European FP7 research project Icarus aiming to develop robotic tools for large scale rescue operations. The tests consisted in the use of the ROAZ unmanned surface vehicle equipped with a precision GPS system for localization and both visible spectrum and IR cameras to detect the target. In the experimental setup, the test human target was deployed in the water wearing a life vest and a diver suit (thus having lower temperature signature in the body except hands and head) and was equipped with a GPS logger. Multiple target approaches were performed in order to test the system with different sun incidence relative angles. The experimental setup, detection method and preliminary results from the field trials performed in the summer of 2013 in Sesimbra, Portugal and in La Spezia, Italy are also presented in this work.

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Oceans - San Diego, 2013

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Oceans - San Diego, 2013

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This work presents an automatic calibration method for a vision based external underwater ground-truth positioning system. These systems are a relevant tool in benchmarking and assessing the quality of research in underwater robotics applications. A stereo vision system can in suitable environments such as test tanks or in clear water conditions provide accurate position with low cost and flexible operation. In this work we present a two step extrinsic camera parameter calibration procedure in order to reduce the setup time and provide accurate results. The proposed method uses a planar homography decomposition in order to determine the relative camera poses and the determination of vanishing points of detected lines in the image to obtain the global pose of the stereo rig in the reference frame. This method was applied to our external vision based ground-truth at the INESC TEC/Robotics test tank. Results are presented in comparison with an precise calibration performed using points obtained from an accurate 3D LIDAR modelling of the environment.