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13th IEEE Global Conference on Consumer Electronic, GCCE 2024

作者： Zhang, Luoxi Xie, Chun Kitahara, Itaru University of Tsukuba Doctoral Program in Empowerment Informatics Tsukuba Japan University of Tsukuba Center for Computational Science Tsukuba Japan

ISBN: (纸本)9798350355079

While scene modeling is widely used in various fields such as VR/AR and 3D art asset creation, it usually requires multiple viewpoint images captured by calibrated cameras, which make difficult to realize practical applications. This paper proposes a method for 3D scene reconstruction from a single snapshot based on RGB-D information without camera parameters. Mask-RCNN are used to separate the foreground and background, and pretrained deep neural network is applied to infer the human mesh of the foreground region. Image inpainting, monocular depth estimation using MiDaS, and point cloud processing are combined to generate the 3D background point cloud. Finally, the foreground and background are integrated to achieve modeling the 3D scene. © 2024 IEEE.

关键词： 3D reconstruction

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One Shot 3D Reconstruction by Observing Multiple Spherical Mirrors 10

One Shot 3D Reconstruction by Observing Multiple Spherical M...

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10th IEEE Global Conference on Consumer Electronics, GCCE 2021

作者： Hiruta, Yuya Shishido, Hidehiko Kitahara, Itaru University of Tsukuba Doctoral Program In Empowerment Informatics Tsukuba Japan University of Tsukuba Center For Computational Sciences Tsukuba Japan

ISBN: (纸本)9781665436762

Since 3D information is helpful to 3D scene observation and recognition, 3D information acquisition and display technologies are used in various fields. Several methods to acquire 3D information such as laser scanner (LiDAR), time of flight (ToF) sensor and 3D photogrammetry from multi-view images are under active development. However, the common disadvantage of these methods is that they require a special equipment or large-scale observation system. This paper proposes a method to estimate 3D information from a monocular image that pseudo captures multi-view images. It utilizes a catadioptric imaging system given by multiple (at least two) curved mirrors and stereo-vision technique. The catadioptric imaging system has a wider field of view than that of a typical camera based on perspective projection. It is suitable for reconstructing 3D information of open spaces with a monocular image. We confirm the quality of estimated 3D information by generating arbitrary viewpoint images. © 2021 IEEE.

关键词： Imaging systems

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3D Reconstruction of Bone from Multi-View X-Ray Images Using Planar Markers 4

3D Reconstruction of Bone from Multi-View X-Ray Images Using...

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4th IEEE Global Conference on Life Sciences and Technologies, LifeTech 2022

作者： Shrestha, Pragyan Xie, Chun Shishido, Hidehiko Yoshii, Yuichi Kitahara, Itaru University of Tsukuba Doctoral Program in Empowerment Informatics Tsukuba Japan University of Tsukuba Center for Computational Sciences Tsukuba Japan Tokyo Medical University Ibaraki Medical Center Ami Japan

ISBN: (纸本)9781665419048

This paper proposes a method to reconstruct 3D bone structure from multi-view X-ray images using a fiducial marker placing five lead balls on a plane attached to the target object. An estimation pipeline for relative pose of the camera and the subject is established to obtain 2D-3D projective geometry for each frame. The target object is rotated such that the planar markers remain in the field of view, to acquire projections images. The 3D voxel volume is reconstructed using the estimated pose as the input to a Simultaneous Algebraic Reconstruction Technique (SART) algorithm. We conduct experiments using a C-arm fluoroscopy of a bone phantom for qualitative evaluation of the proposed method. © 2022 IEEE.

关键词： Image reconstruction

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A 3D Model Generation from a Single Snapshot in Outdoor Scene

A 3D Model Generation from a Single Snapshot in Outdoor Scen...

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IEEE Global Conference on Consumer Electronics (GCCE)

作者： Luoxi Zhang Chun Xie Itaru Kitahara Doctoral Program in Empowerment Informatics University of Tsukuba Tsukuba Japan Center for Computational Science University of Tsukuba Tsukuba Japan

ISBN: (数字)9798350355079

ISBN: (纸本)9798350355086

关键词： Point cloud compression Solid modeling Three-dimensional displays Computational modeling Artificial neural networks Cameras Hardware Image reconstruction Consumer electronics Load modeling

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M3D: Dual-Stream Selective State Spaces and Depth-Driven Framework for High-Fidelity Single-View 3D Reconstruction

arXiv

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arXiv 2024年

作者： Zhang, Luoxi Shrestha, Pragyan Zhou, Yu Xie, Chun Kitahara, Itaru Doctoral Program in Empowerment Informatics University of Tsukuba Japan Center for Computational Science University of Tsukuba Japan Department of Data Science and Artificial Intelligence The Hong Kong Polytechnic University China

The precise reconstruction of 3D objects from a single RGB image in complex scenes presents a critical challenge in virtual reality, autonomous driving, and robotics. Existing neural implicit 3D representation methods face significant difficulties in balancing the extraction of global and local features, particularly in diverse and complex environments, leading to insufficient reconstruction precision and quality. We propose M3D, a novel single-view 3D reconstruction framework, to tackle these challenges. This framework adopts a dual-stream feature extraction strategy based on Selective State Spaces to effectively balance the extraction of global and local features, thereby improving scene comprehension and representation precision. Additionally, a parallel branch extracts depth information, effectively integrating visual and geometric features to enhance reconstruction quality and preserve intricate details. Experimental results indicate that the fusion of multi-scale features with depth information via the dual-branch feature extraction significantly boosts geometric consistency and fidelity, achieving state-of-the-art reconstruction performance. Our code and dataset are publicly available at this URL. © 2024, CC BY-NC-ND.

关键词： 3D reconstruction

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