MScMS-II: an innovative IR-based indoor coordinate measuring system for large-scale metrology applications

According to the current great interest concerning large-scale metrology applications in many different fields of manufacturing industry, technologies and techniques for dimensional measurement have recently shown a substantial improvement. Ease-of-use, logistic and economic issues, as well as metrological performance are assuming a more and more important role among system requirements. This paper describes the architecture and the working principles of a novel infrared (IR) optical-based system, designed to perform low-cost and easy indoor coordinate measurements of large-size objects. The system consists of a distributed network-based layout, whose modularity allows fitting differently sized and shaped working volumes by adequately increasing the number of sensing units. Differently from existing spatially distributed metrological instruments, the remote sensor devices are intended to provide embedded data elaboration capabilities, in order to share the overall computational load. The overall system functionalities, including distributed layout configuration, network self-calibration, 3D point localization, and measurement data elaboration, are discussed. A preliminary metrological characterization of system performance, based on experimental testing, is also presente

RGB-D datasets using microsoft kinect or similar sensors: a survey

RGB-D data has turned out to be a very useful representation of an indoor scene for solving fundamental computer vision problems. It takes the advantages of the color image that provides appearance information of an object and also the depth image that is immune to the variations in color, illumination, rotation angle and scale. With the invention of the low-cost Microsoft Kinect sensor, which was initially used for gaming and later became a popular device for computer vision, high quality RGB-D data can be acquired easily. In recent years, more and more RGB-D image/video datasets dedicated to various applications have become available, which are of great importance to benchmark the state-of-the-art. In this paper, we systematically survey popular RGB-D datasets for different applications including object recognition, scene classification, hand gesture recognition, 3D-simultaneous localization and mapping, and pose estimation. We provide the insights into the characteristics of each important dataset, and compare the popularity and the difficulty of those datasets. Overall, the main goal of this survey is to give a comprehensive description about the available RGB-D datasets and thus to guide researchers in the selection of suitable datasets for evaluating their algorithms

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

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

A novel multi-target modular probe for multiple Large-Volume Metrology systems

Recent studies show that the combined use of Large-Volume Metrology (LVM) systems (e.g., laser trackers, rotary-laser automatic theodolites (R-LATs), photogrammetric cameras, etc.) can lead to a systematic reduction in measurement uncertainty and a better exploitation of the available equipment. Unfortunately, the sensors of a specific LVM system are usually able to localize only specific targets (i.e., active/passive elements positioned in the measurement volume) and not necessarily those related to other systems (e.g., the reflective markers for photogrammetric cameras cannot be used for R-LATs or laser trackers); this represents an obstacle when using combinations of different LVM systems. This paper describes the design of a new modular probe, with different typologies of targets and integrated sensors, which allows to simplify the measurement process. The probe is versatile as the number of targets, their typology and spatial position can be customized depending on the combination of LVM systems in use. A detailed analysis of the technical and functional characteristics of the probe is followed by the presentation of a mathematical/statistical model for the real-time probe localization. Description is supported by realistic application examples

Advanced Endoscopic Navigation:Surgical Big Data,Methodology,and Applications

随着科学技术的飞速发展，健康与环境问题日益成为人类面临的最重大问题之一。信息科学、计算机技术、电子工程与生物医学工程等学科的综合应用交叉前沿课题，研究现代工程技术方法，探索肿瘤癌症等疾病早期诊断、治疗和康复手段。本论文综述了计算机辅助微创外科手术导航、多模态医疗大数据、方法论及其临床应用：从引入微创外科手术导航概念出发，介绍了医疗大数据的术前与术中多模态医学成像方法、阐述了先进微创外科手术导航的核心流程包括计算解剖模型、术中实时导航方案、三维可视化方法及交互式软件技术，归纳了各类微创外科手术方法的临床应用。同时，重点讨论了全球各种手术导航技术在临床应用中的优缺点，分析了目前手术导航领域内的最新技术方法。在此基础上，提出了微创外科手术方法正向数字化、个性化、精准化、诊疗一体化、机器人化以及高度智能化的发展趋势。【Abstract】Interventional endoscopy (e.g., bronchoscopy, colonoscopy, laparoscopy, cystoscopy) is a widely performed procedure that involves either diagnosis of suspicious lesions or guidance for minimally invasive surgery in a variety of organs within the body cavity. Endoscopy may also be used to guide the introduction of certain items (e.g., stents) into the body. Endoscopic navigation systems seek to integrate big data with multimodal information (e.g., computed tomography, magnetic resonance images, endoscopic video sequences, ultrasound images, external trackers) relative to the patient's anatomy, control the movement of medical endoscopes and surgical tools, and guide the surgeon's actions during endoscopic interventions. Nevertheless, it remains challenging to realize the next generation of context-aware navigated endoscopy. This review presents a broad survey of various aspects of endoscopic navigation, particularly with respect to the development of endoscopic navigation techniques. First, we investigate big data with multimodal information involved in endoscopic navigation. Next, we focus on numerous methodologies used for endoscopic navigation. We then review different endoscopic procedures in clinical applications. Finally, we discuss novel techniques and promising directions for the development of endoscopic navigation.X.L. acknowledges funding from the Fundamental Research Funds for the Central Universities. T.M.P. acknowledges funding from the Canadian Foundation for Innovation, the Canadian Institutes for Health Research, the National Sciences and Engineering Research Council of Canada, and a grant from Intuitive Surgical Inc

Context Aware Family Dynamics based Internet of Things Access Control Towards Better Child Safety

Today, children are increasingly connected to the Internet and consume content and services through various means. It has been a challenge for less tech-savvy parents to protect children from harmful content and services. Internet of Things (IoT) has made the situation much worse as IoT devices allow children to connect to the Internet in novel ways (e.g., connected refrigerators, TVs, and so on). In this paper, we propose mySafeHome, an approach which utilises family dynamics to provide a more natural, and intuitive access control mechanism to protect children from harmful content and services in the context of IoT. In mySafeHome, access control dynamically adapts based on the physical distance between family members. For example, a particular type of content can only be consumed, through TV, by children if the parents are in the same room (or hearing distance). mySafeHome allows parents to assess a given content by themselves. Our approach also aims to create granular levels of access control (e.g., block / limit certain content, features, services, on certain devices when the parents are not in the vicinity). We developed a prototype using OpenHAB and several smart home devices to demonstrate the proposed approach. We believe that our approach also facilitates the creation of better relationships between family members. A demo can be viewed here: http://safehome.technology/demo

Real-Time Implementation of Vision-Aided Monocular Navigation for Small Fixed-Wing Unmanned Aerial Systems

The goal of this project was to develop and implement algorithms to demonstrate real-time positioning of a UAV using a monocular camera combined with previously collected orthorectified imagery. Unlike previous tests, this project did not utilize a full inertial navigation system (INS) for attitude, but instead had to rely on the attitude obtained by inexpensive commercial off-the-shelf (COTS) autopilots. The system consisted of primarily COTS components and open-source software, and was own over Camp Atterbury, IN for a sequence of flight tests in Fall 2015. The system obtained valid solutions over much of the flight path, identifying features in the flight image, matching those features with a database of features, and then solving both the 6DOF solution, and an attitude-aided 3DOF solution. The tests demonstrated that such attitude aiding is beneficial, since the horizontal DRMS of the 6DOF solution was 59m, whereas the 3DOF solution DRMS was 15m. Post processing was done to improve the algorithm to correct for system errors, obtaining a 3DOF solution DRMS of 8.22 meters. Overall, this project increased our understanding of the capabilities and limitations of real-time vision-aided navigation, and demonstrated that such navigation is possible on a relatively small platform with limited computational power