64 research outputs found

    Multicamera System for Automatic Positioning of Objects in Game Sports

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    Garantir um sistema com múltiplas câmaras que seja capaz de extrair dados 3D da posição de uma bola durante um evento desportivo, através da análise e teste de técnicas de visão computacional (calibração de câmaras e reconstrução 3D)

    External multi-modal imaging sensor calibration for sensor fusion: A review

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    Multi-modal data fusion has gained popularity due to its diverse applications, leading to an increased demand for external sensor calibration. Despite several proven calibration solutions, they fail to fully satisfy all the evaluation criteria, including accuracy, automation, and robustness. Thus, this review aims to contribute to this growing field by examining recent research on multi-modal imaging sensor calibration and proposing future research directions. The literature review comprehensively explains the various characteristics and conditions of different multi-modal external calibration methods, including traditional motion-based calibration and feature-based calibration. Target-based calibration and targetless calibration are two types of feature-based calibration, which are discussed in detail. Furthermore, the paper highlights systematic calibration as an emerging research direction. Finally, this review concludes crucial factors for evaluating calibration methods and provides a comprehensive discussion on their applications, with the aim of providing valuable insights to guide future research directions. Future research should focus primarily on the capability of online targetless calibration and systematic multi-modal sensor calibration.Ministerio de Ciencia, InnovaciĂłn y Universidades | Ref. PID2019-108816RB-I0

    FPGA-based module for SURF extraction

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    We present a complete hardware and software solution of an FPGA-based computer vision embedded module capable of carrying out SURF image features extraction algorithm. Aside from image analysis, the module embeds a Linux distribution that allows to run programs specifically tailored for particular applications. The module is based on a Virtex-5 FXT FPGA which features powerful configurable logic and an embedded PowerPC processor. We describe the module hardware as well as the custom FPGA image processing cores that implement the algorithm's most computationally expensive process, the interest point detection. The module's overall performance is evaluated and compared to CPU and GPU based solutions. Results show that the embedded module achieves comparable disctinctiveness to the SURF software implementation running in a standard CPU while being faster and consuming significantly less power and space. Thus, it allows to use the SURF algorithm in applications with power and spatial constraints, such as autonomous navigation of small mobile robots

    Scalable 3D video of dynamic scenes

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    In this paper we present a scalable 3D video framework for capturing and rendering dynamic scenes. The acquisition system is based on multiple sparsely placed 3D video bricks, each comprising a projector, two grayscale cameras, and a color camera. Relying on structured light with complementary patterns, texture images and pattern-augmented views of the scene are acquired simultaneously by time-multiplexed projections and synchronized camera exposures. Using space-time stereo on the acquired pattern images, high-quality depth maps are extracted, whose corresponding surface samples are merged into a view-independent, point-based 3D data structure. This representation allows for effective photo-consistency enforcement and outlier removal, leading to a significant decrease of visual artifacts and a high resulting rendering quality using EWA volume splatting. Our framework and its view-independent representation allow for simple and straightforward editing of 3D video. In order to demonstrate its flexibility, we show compositing techniques and spatiotemporal effect

    Study and Characterization of a Camera-based Distributed System for Large-Volume Dimensional Metrology Applications

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    Large-Volume Dimensional Metrology (LVDM) deals with dimensional inspection of large objects with dimensions in the order of tens up to hundreds of meters. Typical large volume dimensional metrology applications concern the assembly/disassembly phase of large objects, referring to industrial engineering. Based on different technologies and measurement principles, a wealth of LVDM systems have been proposed and developed in the literature, just to name a few, e.g., optical based systems such as laser tracker, laser radar, and mechanical based systems such as gantry CMM and multi-joints artificial arm CMM, and so on. Basically, the main existing LVDM systems can be divided into two categories, i.e. centralized systems and distributed systems, according to the scheme of hardware configuration. By definition, a centralized system is a stand-alone unit which works independently to provide measurements of a spatial point, while a distributed system, is defined as a system that consists of a series of sensors which work cooperatively to provide measurements of a spatial point, and usually individual sensor cannot measure the coordinates separately. Some representative distributed systems in the literature are iGPS, MScMS-II, and etc. The current trend of LVDM systems seem to orient towards distributed systems, and actually, distributed systems demonstrate many advantages that distinguish themselves from conventional centralized systems
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