Real-Time High Resolution 3D Data on the HoloLens

Garon, Mathieu; Boulet, Pierre-Olivier; Doironz, Jean-Philippe; Beaulieu, Luc; Lalonde, Jean‐François

doi:10.1109/ismar-adjunct.2016.0073

Cited by 54 publications

(22 citation statements)

References 6 publications

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“…4.1.1 Limitations Striving to be completely portable, these devices unfortunately suffer multiple limitations, such as the lack of battery time (about 180 minutes with full charge), a narrow field of view (35), limited processing capabilities and lack of high quality depth data (Garon et al, 2016). The user interaction is also limited to two gestures, the air tap and the bloom, the later being reserved to exit an application.…”

Section: The Hololensmentioning

confidence: 99%

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Bim Mixed Reality Tool for the Inspection of Heritage Buildings

Brito

Alves

Magalhães

et al. 2019

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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<p><strong>Abstract.</strong> Historical and cultural building conservation is often limited to high value buildings and only receives financial support when serious issues arise. Modern technologies are able to support and encourage a preventive approach, diminishing costs and avoiding possibly irreparable damage. One way of doing so is by improving the work-flow of building inspectors during their inspection r outines. In that regard, mixed reality presents itself as an attractive framework for easing maintenance tasks. This paper describes our current implementation of such a solution, levering the spatial capabilities of Microsoft’s HoloLens glasses. </p>

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Section: The Hololensmentioning

confidence: 99%

“…Spatial mapping data is noisy The reconstruction of the space around the HoloLens is very coarse (Garon et al, 2016). This adds a further layer of difficulty to the problem, as the data would require further processing prior to matching attempts.…”

Section: Model Overlaymentioning

confidence: 99%

Bim Mixed Reality Tool for the Inspection of Heritage Buildings

Brito

Alves

Magalhães

et al. 2019

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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“…When the surrounding environment or objects moved, noise was generated, which lowered tracking accuracy. Therefore, there is a disadvantage that the surrounding environment must be fixed or an additional noise removing step is required [19].…”

Section: Related Workmentioning

confidence: 99%

“…There are two methods to generate this file. In the first method, the 3D position information of the scene is acquired from HoloLens using a sharing server via a network connection [24]. However, this method can be affected by an unstable network connection which can cause errors in the position and rotation data acquired by HoloLens.…”

Section: Real-time Match-moving With Hololensmentioning

confidence: 99%

“…In order to measure the accuracy of proposed and traditional (Boujou) methods in terms of match-moving, we compared them against the ground truth. It is well-known fact that the match-moving results highly depend on the accuracy of camera trajectory [19]. In order to measure the accuracy of camera trajectory extracted from both the proposed and traditional methods, we compared them against the Oculus Rift's camera trajectory as ground truth.…”

Section: Experimental Environmentmentioning

confidence: 99%

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A Novel Real-Time Match-Moving Method with HoloLens

et al. 2019

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With the advancement of media and computing technologies, video compositing techniques have improved to a great extent. These techniques have been used not only in the entertainment industry but also in advertisement and new media. Match-moving is a cinematic technology in virtual-real image synthesis that allows the insertion of computer graphics (virtual objects) into real world scenes. To make a realistic virtual-real image synthesis, it is important to obtain internal parameters (such as focal length) and external parameters (position and rotation) from an Red-Green-Blue(RGB) camera. Conventional methods recover these parameters by extracting feature points from recorded video frames to guide the virtual camera. These methods fail when there is occlusion or motion blur in the recorded scene. In this paper, we propose a novel method (system) for pre-visualization and virtual-real image synthesis that overcomes the limitations of conventional methods. This system uses the spatial understanding principle of Microsoft HoloLens to perform the match-moving of virtual-real video scenes. Experimental results demonstrate that our system is much more accurate and efficient than existing systems for video compositing.

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