A Low-Cost, Flexible and Portable Volumetric Capturing System

Sterzentsenko, Vladimiros; Karakottas, Antonis; Papachristou, Alexandros; Zioulis, Nikolaos; Doumanoglou, Alexandros; Zarpalas, Dimitrios; Daras, Petros

doi:10.1109/sitis.2018.00038

Cited by 24 publications

(24 citation statements)

References 29 publications

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“…Furthermore, the software is factory calibrated in order to use the temperature information provided by the internal sensors and modify the data accordingly [16]. All the mentioned motion and positional features indicate that the ZED 2i depth camera is extremely suitable for development of autonomous and industrial robotic applications [21][22][23][24][25][26][27][28][29][30][31][32][33][34][35][36][37][38][39][40].…”

Section: Zed Depth Sensorsmentioning

confidence: 99%

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Perspectives of RealSense and ZED Depth Sensors for Robotic Vision Applications

et al. 2022

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This review paper presents an overview of depth cameras. Our goal is to describe the features and capabilities of the introduced depth sensors in order to determine their possibilities in robotic applications, focusing on objects that might appear in applications with high accuracy requirements. A series of experiments was conducted, and various depth measuring conditions were examined in order to compare the measurement results of all the depth cameras. Based on the results, all the examined depth sensors were appropriate for applications where obstacle avoidance and robot spatial orientation were required in coexistence with image vision algorithms. In robotic vision applications where high accuracy and precision were obligatory, the ZED depth sensors achieved better measurement results.

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Section: Zed Depth Sensorsmentioning

confidence: 99%

“…For this purpose, 3D optical systems have been successfully implemented in multifarious scientific fields such as robotics, car manufacturing, automatics, mechanics, biomedicine, surveillance systems, industry, etc. [21][22][23][24][25][26][27][28][29][30][31][32][33][34][35][36][37][38][39][40].…”

Section: Introductionmentioning

confidence: 99%

Perspectives of RealSense and ZED Depth Sensors for Robotic Vision Applications

et al. 2022

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“…It is worth noting that we configured the sensors exploiting their spatial filtering and exposure adjustment capabilities to capture the best possible depth quality. We captured the mRGBD data using the capturing system 2 proposed by Sterzentsenko et al [46], while spatial alignment between the sensors was achieved using the multi-sensor calibration schema proposed by Papachristou et al [47]. HW-SYNCed mRGBD samples are depicted in Fig.…”

Section: B Dataset Creationmentioning

confidence: 99%

HUMAN4D: A Human-Centric Multimodal Dataset for Motions and Immersive Media

et al. 2020

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We introduce HUMAN4D, a large and multimodal 4D dataset that contains a variety of human activities simultaneously captured by a professional marker-based MoCap, a volumetric capture and an audio recording system. By capturing 2 female and 2 male professional actors performing various fullbody movements and expressions, HUMAN4D provides a diverse set of motions and poses encountered as part of single-and multi-person daily, physical and social activities (jumping, dancing, etc.), along with multi-RGBD (mRGBD), volumetric and audio data. Despite the existence of multi-view color datasets captured with the use of hardware (HW) synchronization, to the best of our knowledge, HUMAN4D is the first and only public resource that provides volumetric depth maps with high synchronization precision due to the use of intra-and inter-sensor HW-SYNC. Moreover, a spatio-temporally aligned scanned and rigged 3D character complements HUMAN4D to enable joint research on time-varying and highquality dynamic meshes. We provide evaluation baselines by benchmarking HUMAN4D with state-of-theart human pose estimation and 3D compression methods. We apply OpenPose and AlphaPose reaching 70.02% and 82.95% mAP PCKh-0.5 on single-and 68.48% and 73.94% mAP PCKh-0.5 on two-person 2D pose estimation, respectively. In 3D pose, a recent multi-view approach named Learnable Triangulation, achieves 80.26% mAP PCK3D-10cm. For 3D compression, we benchmark Draco, Corto and CWIPC open-source 3D codecs, respecting online encoding and steady bit-rates between 7-155 and 2-90 Mbps for mesh-and pointbased volumetric video, respectively. Qualitative and quantitative visual comparison between mesh-based volumetric data reconstructed in different qualities and captured RGB, showcases the available options with respect to 4D representations. HUMAN4D is introduced to enable joint research on spatio-temporally aligned pose, volumetric, mRGBD and audio data cues. The dataset and its code are available online.

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“…The CapTion toolkit comprises a set of tools designed for mixed reality media productions that aim to combine two types of Free-Viewpoint Video (FVV), namely 360 • and 3D content. The first system of the tool-chain is an affordable and portable volumetric capturing hardware system with its corresponding software application [3], which gives the ability to record spatially calibrated [4] and temporally aligned RGB-D videos. It is followed by the Performance Capture application which produces dynamic (i.e.…”

Section: Caption and 3d Mentormentioning

confidence: 99%

The Hyper360 toolset for enriched 360$^\circ$ video

Fassold,

Karakottas,

Tsatsou

et al. 2020

Preprint

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360• video is a novel media format, rapidly becoming adopted in media production and consumption as part of todays ongoing virtual reality revolution. Due to its novelty, there is a lack of tools for producing highly engaging 360 • video for consumption on a multitude of platforms. In this work, we describe the work done so far in the Hyper360 project on tools for 360 • video. Furthermore, the first pilots which have been produced with the Hyper360 tools are presented.

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A Low-Cost, Flexible and Portable Volumetric Capturing System

Cited by 24 publications

References 29 publications

Perspectives of RealSense and ZED Depth Sensors for Robotic Vision Applications

Perspectives of RealSense and ZED Depth Sensors for Robotic Vision Applications

HUMAN4D: A Human-Centric Multimodal Dataset for Motions and Immersive Media

The Hyper360 toolset for enriched 360$^\circ$ video

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