Assessment of Optical See-Through Head Mounted Display Calibration for Interactive Augmented Reality

Ballestin, Giorgio; Chessa, Manuela; Solari, Fabio

doi:10.1109/iccvw.2019.00546

Cited by 4 publications

(6 citation statements)

References 18 publications

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“…4): we assume that the error is compensated by a scale factor introduced by a focal length drift with respect to the real one. For more details about the OST calibration and validation, refer to [49]. The proposed approach is considered to be suitable to register an OST HMD inside the HTC Vive Lighthouse system, and without loss of generality to other similar systems that allow the precise positioning of trackers (i.e.…”

Section: F Framework Discussionmentioning

confidence: 99%

“…This also applies to the users' fingers and hands, if the interaction is quantified as well. The procedure developed in [49] has been improved and generalized to also work for VST, and can be extended to any VST or OST headworn device.…”

Section: Discussionmentioning

confidence: 99%

“…To perform the OST HMD calibration, we used the popular SPAAM technique [48], as the Meta HMD has no eyetracking sensors to be used for automatic calibration methods. For more insight on the SPAAM technique, refer to [48], [49], since we aim to provide a registration framework that allows having a common reference frame for different devices and real objects, not to devise a new calibration procedure for OST HMDs. Independent of the type of calibration, the purpose is to find the transformation matrix that can map HMD pixel coordinates to the user's eyes' coordinates.…”

Section: A Ost Registrationmentioning

confidence: 99%

“…To quantify the OST residual calibration error, we performed several calibrations with a mannequin as described in [49] (see Fig. 3a).…”

Section: E Residual Alignment Errormentioning

confidence: 99%

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A Registration Framework for the Comparison of Video and Optical See-Through Devices in Interactive Augmented Reality

2021

Self Cite

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In this paper, we designed a registration framework that can be used to develop augmented reality environments, where all the real (including the users) and virtual elements are co-localized and registered in a common reference frame. The software is provided together with this paper, to contribute to the research community. The developed framework allows us to perform a quantitative assessment of interaction and egocentric perception in Augmented Reality (AR) environments. We assess perception and interaction in the peripersonal space through a 3D blind reaching task in a simple scenario and an interaction task in a kitchen scenario using both video (VST) and optical see-through (OST) head-worn technologies. Moreover, we carry out the same 3D blind reaching task in real condition (without head-mounted display and reaching real targets). This provides a baseline performance with which to compare the two augmented reality technologies. The blind reaching task results show an underestimation of distances with OST devices and smaller estimation errors in frontal spatial positions when the depth does not change. This happens with both OST and VST devices, compared with the real-world baseline. Such errors are compensated in the interaction kitchen scenario task. Thanks to the egocentric viewing geometry and the specific required task, which constrain the position perception on a table, both VST and OST have comparable and effective performance. Thus, our results show that such technologies have issues, though they can be effectively used in specific real tasks. This does not allow us to choose between VST and OST devices. Still, it provides a baseline and a registration framework for further studies and emphasizes the specificity of perception in interactive AR.

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Section: F Framework Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: A Ost Registrationmentioning

confidence: 99%

“…To quantify the OST residual calibration error, we performed several calibrations with a mannequin as described in [49] (see Fig. 3a).…”

Section: E Residual Alignment Errormentioning

confidence: 99%

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A Registration Framework for the Comparison of Video and Optical See-Through Devices in Interactive Augmented Reality

2021

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“…In (Ballestin et al, 2019) the calibration process of an optical see-through device, based on a visual alignment method, was described. Recently, one such augmented reality system has been developed for a helicopter pilot assistance (Walko, Peinecke, 2020).…”

Section: Head-up Projection Systemsmentioning

confidence: 99%

Synthetic Vision System Calibration for Conform Projection on the Pilot’s Head-Up Display

Danilov

Kozyrev

Grechanichenko

et al. 2020

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. Situational awareness of the crew is critical for the safety of the air flight. Head-up display allows providing all required flight information in front of the pilot over the cockpit view visible through the cockpit’s front window. This device has been created for solving the problem of informational overload during piloting of an aircraft. While computer graphics such as scales and digital terrain model can be easily presented on the such display, errors in the Head-up display alignment for correct presenting of sensor data pose challenges. The main problem arises from the parallax between the pilot’s eyes and the position of the camera. This paper is focused on the development of an online calibration algorithm for conform projection of the 3D terrain and runway models on the pilot’s head-up display. The aim of our algorithm is to align the objects visible through the cockpit glass with their projections on the Head-up display. To improve the projection accuracy, we use an additional optical sensor installed on the aircraft. We combine classical photogrammetric techniques with modern deep learning approaches. Specifically, we use an object detection neural network model to find the runway area and align runway projection with its actual location. Secondly, we re-project the sensor’s image onto the 3D model of the terrain to eliminate errors caused by the parallax. We developed an environment simulator to evaluate our algorithm. Using the simulator we prepared a large training dataset. The dataset includes 2000 images of video sequences representing aircraft’s motion during takeoff, landing and taxi. The results of the evaluation are encouraging and demonstrate both qualitatively and quantitatively that the proposed algorithm is capable of precise alignment of the 3D models projected on a Head-up display.

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Trajectory-based Calibration for Optical See-Through Head-Mounted Displays Without Alignment

Wang,

Zhao,

Chen

et al. 2024

Lecture Notes in Computer Science

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Assessment of Optical See-Through Head Mounted Display Calibration for Interactive Augmented Reality

Cited by 4 publications

References 18 publications

A Registration Framework for the Comparison of Video and Optical See-Through Devices in Interactive Augmented Reality

A Registration Framework for the Comparison of Video and Optical See-Through Devices in Interactive Augmented Reality

Synthetic Vision System Calibration for Conform Projection on the Pilot’s Head-Up Display

Trajectory-based Calibration for Optical See-Through Head-Mounted Displays Without Alignment

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