Wide-area augmented reality using camera tracking and mapping in multiple regions

Castle, Robert O.; Klein, Georg; Murray, David

doi:10.1016/j.cviu.2011.02.007

Cited by 45 publications

(15 citation statements)

References 29 publications

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“…One exception to this has been the extension to PTAM developed by Castle et al [10] to permit several cameras to work in multiple maps, both separately or simultaneously. Here the approach to dealing with large-scale environments is to permit the user to decide what regions to map.…”

Section: Related Workmentioning

confidence: 99%

Real-time 6-DOF multi-session visual SLAM over large-scale environments

McDonald

Kaess

Cadena

et al. 2013

Robotics and Autonomous Systems

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a b s t r a c tThis paper describes a system for performing real-time multi-session visual mapping in large-scale environments. Multi-session mapping considers the problem of combining the results of multiple simultaneous localisation and mapping (SLAM) missions performed repeatedly over time in the same environment. The goal is to robustly combine multiple maps in a common metrical coordinate system, with consistent estimates of uncertainty. Our work employs incremental smoothing and mapping (iSAM) as the underlying SLAM state estimator and uses an improved appearance-based method for detecting loop closures within single mapping sessions and across multiple sessions. To stitch together pose graph maps from multiple visual mapping sessions, we employ spatial separator variables, called anchor nodes, to link together multiple relative pose graphs.The system architecture consists of a separate front-end for computing visual odometry and windowed bundle adjustment on individual sessions, in conjunction with a back-end for performing the place recognition and multi-session mapping. We provide experimental results for real-time multisession visual mapping on wheeled and handheld datasets in the MIT Stata Center. These results demonstrate key capabilities that will serve as a foundation for future work in large-scale persistent visual mapping.

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Section: Related Workmentioning

confidence: 99%

Real-time 6-DOF multi-session visual SLAM over large-scale environments

McDonald

Kaess

Cadena

et al. 2013

Robotics and Autonomous Systems

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“…Before overlaying dynamic virtual content onto a real-world environment, it is necessary for an AR system to be able to sense its working environment and track a user's position relative to the recognized model or its surroundings such as 3 positioning variables (x, y, z) and 3 rotating variables (raw, pitch, roll). This is referred to as the AR tracking problem [1]. Over recent decades, researchers have developed several advanced vision-based pose-tracking algorithms to define 2D/3D relationships through images, which could be divided into three phases.…”

Section: Monitor-based Applicationsmentioning

confidence: 99%

“…After then, AR annotation has been frequently adopted in basketball, tennis, ice hockey, etc. [1,3,4].…”

Section: Monitor-based Applicationsmentioning

confidence: 99%

Application of Augmented Reality and Robotic Technology in Broadcasting: A Survey

Yan

2017

Robotics

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Abstract:As an innovation technique, Augmented Reality (AR) has been gradually deployed in the broadcast, videography and cinematography industries. Virtual graphics generated by AR are dynamic and overlap on the surface of the environment so that the original appearance can be greatly enhanced in comparison with traditional broadcasting. In addition, AR enables broadcasters to interact with augmented virtual 3D models on a broadcasting scene in order to enhance the performance of broadcasting. Recently, advanced robotic technologies have been deployed in a camera shooting system to create a robotic cameraman so that the performance of AR broadcasting could be further improved, which is highlighted in the paper.

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“…This module includes tracking thread and mapping thread, partially inspired from the framework of PTAM [8,9]. However, FAST corner based registration [10] is substituted by our ultra-low-weight registration algorithm [11].…”

Section: Real-time Fov Matchingmentioning

confidence: 99%

Intrusion Detection and Cooperative Tracking Using PTZ Network Thermal Imagers

Yang

Han

et al. 2015

International Journal of Distributed Sensor Networks

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Nowadays more and more network thermal imaging cameras are working over distributed networks, offering the capability of online remote intelligent video surveillance. In this paper, we propose an original intrusion detection and cooperative tracking approach applied for PTZ (Pan/Tilt/Zoom) network thermal imagers. It consists of three modules. The key module is the real-time FOV (Field of View) matching module, which is realized in a parallel way. The intrusion detection module first eliminates the offset between current frame and prior frame through FOV matching and then handles intrusion detection by motion detection in the preset surveillance zone. The cooperative tracking module shifts the priority of tracking by imager pose estimation, which is also based on FOV matching, avoiding transferring the local features from one imager to another. Experiments are conducted to demonstrate that the proposed approach is of high accuracy for intrusion detection and cooperative tracking and keeps the frame rate over 20 fps.

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Wide-area augmented reality using camera tracking and mapping in multiple regions

Cited by 45 publications

References 29 publications

Real-time 6-DOF multi-session visual SLAM over large-scale environments

Real-time 6-DOF multi-session visual SLAM over large-scale environments

Application of Augmented Reality and Robotic Technology in Broadcasting: A Survey

Intrusion Detection and Cooperative Tracking Using PTZ Network Thermal Imagers

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