Accuracy Analysis of Augmented Reality Markers for Visual Mapping and Localization

Xavier, Rodrigo S.; Silva, Bruno Marques Ferreira da; Gonalves, Luiz M. G.

doi:10.1109/wvc.2017.00020

Cited by 12 publications

(10 citation statements)

References 14 publications

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“…In publication [13] the Authors used Aruco markers for visual SLAM and concluded that the mean positioning error is less than 2% calculated from the distance camera-marker. In the distance equal 2.5m the positioning error is less than 5cm which is the same as in previous publication.…”

Section: Results Discussionmentioning

confidence: 99%

Overhead Vision System for Testing Swarms and Groups of Wheeled Robots

Wiech

Hendzel

2019

JAMRIS

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The paper describes how to use ArUco markers to determine the posi�on and orienta�on o� wheeled robots in �� space. �t is preceded b� a general descrip�on o� the testbed and a detailed descrip�on o� the marker detec�on algorithm along with the camera calibra�on using the ChaArUco markers. The camera has been described and calibrated using the pinhole camera model, taking into account distor�on o� the lens. The second part o� the ar-�cle describes the wheeled robots with their mechanical construc�on.

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Section: Results Discussionmentioning

confidence: 99%

Overhead Vision System for Testing Swarms and Groups of Wheeled Robots

Wiech

Hendzel

2019

JAMRIS

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“…The accuracy in estimating localization and rotation of each ArUco marker depends on many factors; among them, the size in pixels, the viewing angle, and the region contrast play a major role. In our application, the distance of the markers varies in a short range and the whole environment is well illuminated; some difficulties in accurate detection can arise from oblique rotations, however, according to [21][22][23] the rotation estimation error, in a similar environment, is within ±1 deg. However, as detailed below, in our application we estimate the average rotation of trunk and head from the average of multiple markers, further reducing the estimation error.…”

Section: Marker Tracking and Analysismentioning

confidence: 99%

Posture Assessment in Dentistry for Different Visual Aids Using 2D Markers

Pispero

Marcon

Ghezzi

et al. 2021

Sensors

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Attention and awareness towards musculoskeletal disorders (MSDs) in the dental profession has increased considerably in the last few years. From recent literature reviews, it appears that the prevalence of MSDs in dentists concerns between 64 and 93%. In our clinical trial, we have assessed the dentist posture during the extraction of 90 third lower molars depending on whether the operator performs the intervention by the use of the operating microscope, surgical loupes, or with the naked eye. In particular, we analyzed the evolution of the body posture during different interventions evaluating the impact of visual aids with respect to naked eye interventions. The presented posture assessment approach is based on 3D acquisitions of the upper body, based on planar markers, which allows us to discriminate spatial displacements up to 2 mm in translation and 1 degree in rotation. We found a significant reduction of neck bending in interventions using visual aids, in particular for those performed with the microscope. We further investigated the impact of different postures on MSD risk using a widely adopted evaluation tool for ergonomic investigations of workplaces, named (RULA) Rapid Upper Limb Assessment. The analysis performed in this clinical trial is based on a 3D marker tracker that is able to follow a surgeon’s upper limbs during interventions. The method highlighted pros and cons of different approaches.

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“…In this approach, a camera and some type of marker is used, and the visual information is only shown when the marker is detected by a device using image or pattern recognition [ 8 ]. Ensuring that markers are detected with minimal latency time is a major challenge, and factors such as brightness and distance can affect marker recognition time [ 9 , 10 ].…”

Section: Related Workmentioning

confidence: 99%

SAR.IoT: Secured Augmented Reality for IoT Devices Management

Fuentes

Correia

Costa

et al. 2021

Sensors

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Currently, solutions based on the Internet of Things (IoT) concept are increasingly being adopted in several fields, namely, industry, agriculture, and home automation. The costs associated with this type of equipment is reasonably small, as IoT devices usually do not have output peripherals to display information about their status (e.g., a screen or a printer), although they may have informative LEDs, which is sometimes insufficient. For most IoT devices, the price of a minimalist display, to output and display the device’s running status (i.e., what the device is doing), might cost much more than the actual IoT device. Occasionally, it might become necessary to visualize the IoT device output, making it necessary to find solutions to show the hardware output information in real time, without requiring extra equipment, only what the administrator usually has with them. In order to solve the above, a technological solution that allows for the visualization of IoT device information in actual time, using augmented reality and a simple smartphone, was developed and analyzed. In addition, the system created integrates a security layer, at the level of AR, to secure the shown data from unwanted eyes. The results of the tests carried out allowed us to validate the operation of the solution when accessing the information of the IoT devices, verify the operation of the security layer in AR, analyze the interaction between smartphones, the platform, and the devices, and check which AR markers are most optimized for this use case. This work results in a secure augmented reality solution, which can be used with a simple smartphone, to monitor / manage IoT devices in industrial, laboratory or research environments.

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Accuracy Analysis of Augmented Reality Markers for Visual Mapping and Localization

Cited by 12 publications

References 14 publications

Overhead Vision System for Testing Swarms and Groups of Wheeled Robots

Overhead Vision System for Testing Swarms and Groups of Wheeled Robots

Posture Assessment in Dentistry for Different Visual Aids Using 2D Markers

SAR.IoT: Secured Augmented Reality for IoT Devices Management

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