10,523 research outputs found
Pivot calibration concept for sensor attached mobile c-arms
Medical augmented reality has been actively studied for decades and many
methods have been proposed torevolutionize clinical procedures. One example is
the camera augmented mobile C-arm (CAMC), which providesa real-time video
augmentation onto medical images by rigidly mounting and calibrating a camera
to the imagingdevice. Since then, several CAMC variations have been suggested
by calibrating 2D/3D cameras, trackers, andmore recently a Microsoft HoloLens
to the C-arm. Different calibration methods have been applied to establishthe
correspondence between the rigidly attached sensor and the imaging device. A
crucial step for these methodsis the acquisition of X-Ray images or 3D
reconstruction volumes; therefore, requiring the emission of ionizingradiation.
In this work, we analyze the mechanical motion of the device and propose an
alternatative methodto calibrate sensors to the C-arm without emitting any
radiation. Given a sensor is rigidly attached to thedevice, we introduce an
extended pivot calibration concept to compute the fixed translation from the
sensor tothe C-arm rotation center. The fixed relationship between the sensor
and rotation center can be formulated as apivot calibration problem with the
pivot point moving on a locus. Our method exploits the rigid C-arm
motiondescribing a Torus surface to solve this calibration problem. We explain
the geometry of the C-arm motion andits relation to the attached sensor,
propose a calibration algorithm and show its robustness against noise, as
wellas trajectory and observed pose density by computer simulations. We discuss
this geometric-based formulationand its potential extensions to different C-arm
applications.Comment: Accepted for Image-Guided Procedures, Robotic Interventions, and
Modeling 2020, Houston, TX, US
GPU-based Image Analysis on Mobile Devices
With the rapid advances in mobile technology many mobile devices are capable
of capturing high quality images and video with their embedded camera. This
paper investigates techniques for real-time processing of the resulting images,
particularly on-device utilizing a graphical processing unit. Issues and
limitations of image processing on mobile devices are discussed, and the
performance of graphical processing units on a range of devices measured
through a programmable shader implementation of Canny edge detection.Comment: Proceedings of Image and Vision Computing New Zealand 201
A software framework for the development of projection-based augmented reality systems
Despite the large amount of methods and applications of augmented reality, there is little homogenization on the software platforms that support them. An exception may be the low level control software that is provided by some high profile vendors such as Qualcomm and Metaio. However, these provide fine grain modules for e.g. element tracking. We are more concerned on the application framework, that includes the control of the devices working together for the development of the AR experience. In this paper we present a software framework that can be used for the development of AR applications based on camera-projector pairs, that is suitable for both fixed, and nomadic setups.Peer ReviewedPostprint (author's final draft
In-home and remote use of robotic body surrogates by people with profound motor deficits
By controlling robots comparable to the human body, people with profound
motor deficits could potentially perform a variety of physical tasks for
themselves, improving their quality of life. The extent to which this is
achievable has been unclear due to the lack of suitable interfaces by which to
control robotic body surrogates and a dearth of studies involving substantial
numbers of people with profound motor deficits. We developed a novel, web-based
augmented reality interface that enables people with profound motor deficits to
remotely control a PR2 mobile manipulator from Willow Garage, which is a
human-scale, wheeled robot with two arms. We then conducted two studies to
investigate the use of robotic body surrogates. In the first study, 15 novice
users with profound motor deficits from across the United States controlled a
PR2 in Atlanta, GA to perform a modified Action Research Arm Test (ARAT) and a
simulated self-care task. Participants achieved clinically meaningful
improvements on the ARAT and 12 of 15 participants (80%) successfully completed
the simulated self-care task. Participants agreed that the robotic system was
easy to use, was useful, and would provide a meaningful improvement in their
lives. In the second study, one expert user with profound motor deficits had
free use of a PR2 in his home for seven days. He performed a variety of
self-care and household tasks, and also used the robot in novel ways. Taking
both studies together, our results suggest that people with profound motor
deficits can improve their quality of life using robotic body surrogates, and
that they can gain benefit with only low-level robot autonomy and without
invasive interfaces. However, methods to reduce the rate of errors and increase
operational speed merit further investigation.Comment: 43 Pages, 13 Figure
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