Cloud-based collaborative 3D reconstruction using smartphones

Poiesi, Fabio; Locher, Alex; Chippendale, Paul; Nocerino, Erica; Remondino, Fabio; Gool, Luc Van

doi:10.1145/3150165.3150166

Cited by 27 publications

(16 citation statements)

References 20 publications

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“…Two pipelines are under testing: the first, described in Poiesi et al (2017) and Nocerino et al (2017) is based on approaches proposed by Sweeney et al (2015), Schonberger et al (2016), Locher et al (2016a) and Locher et al (2016b). The second procedure, hereafter presented, follows the SfM/DIM pipeline presented by Schonberger and Frahm (2016).…”

Section: Orientation and 3d Reconstructionmentioning

confidence: 99%

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3d Reconstruction With a Collaborative Approach Based on Smartphones and a Cloud-Based Server

Nocerino

Poiesi

Locher

et al. 2017

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

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ABSTRACT:The paper presents a collaborative image-based 3D reconstruction pipeline to perform image acquisition with a smartphone and geometric 3D reconstruction on a server during concurrent or disjoint acquisition sessions. Images are selected from the video feed of the smartphone's camera based on their quality and novelty. The smartphone's app provides on-the-fly reconstruction feedback to users co-involved in the acquisitions. The server is composed of an incremental SfM algorithm that processes the received images by seamlessly merging them into a single sparse point cloud using bundle adjustment. Dense image matching algorithm can be lunched to derive denser point clouds. The reconstruction details, experiments and performance evaluation are presented and discussed.

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Section: Orientation and 3d Reconstructionmentioning

confidence: 99%

“…The second approach, presented in Poiesi el al. (2017), is based on a two-step procedure, where the interior and exterior orientation parameters are refined as follows. Images acquired in the same session and using same device are forced to share the same camera calibration parameters in the adjustment procedure.…”

Section: Collaborative Approachmentioning

confidence: 99%

3d Reconstruction With a Collaborative Approach Based on Smartphones and a Cloud-Based Server

Nocerino

Poiesi

Locher

et al. 2017

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

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“…Snapshots, or captured frames, can be taken either periodically (Knapitsch et al, 2017), or dynamically based on scene content (Resch et al, 2015;Poiesi et al, 2017). Frame captures based on scene content is desirable because one can avoid excessive data traffic when a scene is still and then capture fast dynamics by increasing the rate when high activity is observed.…”

Section: Related Workmentioning

confidence: 99%

Multi-view Data Capture using Edge-synchronised Mobiles

Bortolon

Chippendale

Messelodi

et al. 2020

Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Application

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Multi-view data capture permits free-viewpoint video (FVV) content creation. To this end, several users must capture video streams, calibrated in both time and pose, framing the same object/scene, from different viewpoints. New-generation network architectures (e.g. 5G) promise lower latency and larger bandwidth connections supported by powerful edge computing, properties that seem ideal for reliable FVV capture. We have explored this possibility, aiming to remove the need for bespoke synchronisation hardware when capturing a scene from multiple viewpoints, making it possible through off-the-shelf mobiles. We propose a novel and scalable data capture architecture that exploits edge resources to synchronise and harvest frame captures. We have designed an edge computing unit that supervises the relaying of timing triggers to and from multiple mobiles, in addition to synchronising frame harvesting. We empirically show the benefits of our edge computing unit by analysing latencies and show the quality of 3D reconstruction outputs against an alternative and popular centralised solution based on Unity3D.

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“…As already shown in several works in the literature (Poiesi et al, 2017), the standard smartphone camera can be conveniently used as an imaging sensor to obtain 3D photogrammetric models of the objects of interest. However, certain external information should be added in order to obtain a metric reconstruction (Alsubaie et al, 2017).…”

Section: Smartphone Stereo-visionmentioning

confidence: 99%

Initial Evaluation of the Potential of Smartphone Stereo-Vision in Museum Visits

Masiero

Tucci

Conti

et al. 2019

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

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<p><strong>Abstract.</strong> The recent introduction of new technologies such as augmented reality, machine learning and the worldwide spread of mobile devices provided with imaging, navigation sensors and high computational power can be exploited in order to drammatically change the museum visit experience. Differently from the traditional use of museum docents or audio guides, the introduction of digital technologies already proved to be useful in order to improve the interest of the visitor thanks to the increased interaction and involvement, reached also by means of visual effects and animations. Actually, the availability of 3D representations, augmented reality and navigation abilities directly on the visitor’s device can lead to a personalized visit, enabling the visitor to have an experience tailored on his/her needs. In this framework, this paper aims at investigating the potentialities of smartphone stereo-vision to improve the geometric information about the artworks available on the visitor’s device. More specifically, in this work smartphone stereo-vision will used as a 3D model generation tool in a 3D artwork recognition system based on a neural network classifier.</p>

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Cloud-based collaborative 3D reconstruction using smartphones

Cited by 27 publications

References 20 publications

3d Reconstruction With a Collaborative Approach Based on Smartphones and a Cloud-Based Server

3d Reconstruction With a Collaborative Approach Based on Smartphones and a Cloud-Based Server

Multi-view Data Capture using Edge-synchronised Mobiles

Initial Evaluation of the Potential of Smartphone Stereo-Vision in Museum Visits

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