A Robust and Real-Time Full 3D Reconstruction Method Based on Multiple Kinect

3D reconstruction techniques for animated images and animation techniques for faces are important research in computer graphics-related fields. Traditional 3D reconstruction techniques for animated images mainly rely on expensive 3D scanning equipment and a lot of time-consuming postprocessing manually and require the scanned animated subject to remain in a fixed pose for a considerable period. In recent years, the development of large-scale computing power of computer-related hardware, especially distributed computing, has made it possible to come up with a real-time and efficient solution. In this paper, we propose a 3D reconstruction method for multivisual animated images based on Poisson’s equation theory. The calibration theory is used to calibrate the multivisual animated images, obtain the internal and external parameters of the camera calibration module, extract the feature points from the animated images of each viewpoint by using the corner point detection operator, then match and correct the extracted feature points by using the least square median method, and complete the 3D reconstruction of the multivisual animated images. The experimental results show that the proposed method can obtain the 3D reconstruction results of multivisual animation images quickly and accurately and has certain real-time and reliability.

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A 3D Reconstruction Method Using Multisensor Fusion in Large-Scale Indoor Scenes

Complexity ◽

10.1155/2020/6973790 ◽

2020 ◽

Vol 2020 ◽

pp. 1-14

Author(s):

Panlong Gu ◽

Fengyu Zhou ◽

Dianguo Yu ◽

Fang Wan ◽

Wei Wang ◽

...

Keyword(s):

3D Reconstruction ◽

Real Time ◽

Large Scale ◽

Reconstruction Method ◽

Loop Closure ◽

Mapping Algorithm ◽

Localization And Mapping ◽

Indoor Scenes ◽

Slam Algorithm ◽

Robot Position

RGBD camera-based VSLAM (Visual Simultaneous Localization and Mapping) algorithm is usually applied to assist robots with real-time mapping. However, due to the limited measuring principle, accuracy, and distance of the equipped camera, this algorithm has typical disadvantages in the large and dynamic scenes with complex lightings, such as poor mapping accuracy, easy loss of robot position, and much cost on computing resources. Regarding these issues, this paper proposes a new method of 3D interior construction, which combines laser radar and an RGBD camera. Meanwhile, it is developed based on the Cartographer laser SLAM algorithm. The proposed method mainly takes two steps. The first step is to do the 3D reconstruction using the Cartographer algorithm and RGBD camera. It firstly applies the Cartographer algorithm to calculate the pose of the RGBD camera and to generate a submap. Then, a real-time 3D point cloud generated by using the RGBD camera is inserted into the submap, and the real-time interior construction is finished. The second step is to improve Cartographer loop-closure quality by the visual loop-closure for the sake of correcting the generated map. Compared with traditional methods in large-scale indoor scenes, the proposed algorithm in this paper shows higher precision, faster speed, and stronger robustness in such contexts, especially with complex light and dynamic objects, respectively.

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Real-Time 3D Reconstruction Method Based on Monocular Vision

Sensors ◽

10.3390/s21175909 ◽

2021 ◽

Vol 21 (17) ◽

pp. 5909

Author(s):

Qingyu Jia ◽

Liang Chang ◽

Baohua Qiang ◽

Shihao Zhang ◽

Wu Xie ◽

...

Keyword(s):

3D Reconstruction ◽

Real Time ◽

Visual Information ◽

Three Dimensional ◽

Position Estimation ◽

Monocular Vision ◽

Cluster Center ◽

Reconstruction Method ◽

The Real ◽

Depth Measurement

Real-time 3D reconstruction is one of the current popular research directions of computer vision, and it has become the core technology in the fields of virtual reality, industrialized automatic systems, and mobile robot path planning. Currently, there are three main problems in the real-time 3D reconstruction field. Firstly, it is expensive. It requires more varied sensors, so it is less convenient. Secondly, the reconstruction speed is slow, and the 3D model cannot be established accurately in real time. Thirdly, the reconstruction error is large, which cannot meet the requirements of scenes with accuracy. For this reason, we propose a real-time 3D reconstruction method based on monocular vision in this paper. Firstly, a single RGB-D camera is used to collect visual information in real time, and the YOLACT++ network is used to identify and segment the visual information to extract part of the important visual information. Secondly, we combine the three stages of depth recovery, depth optimization, and deep fusion to propose a three-dimensional position estimation method based on deep learning for joint coding of visual information. It can reduce the depth error caused by the depth measurement process, and the accurate 3D point values of the segmented image can be obtained directly. Finally, we propose a method based on the limited outlier adjustment of the cluster center distance to optimize the three-dimensional point values obtained above. It improves the real-time reconstruction accuracy and obtains the three-dimensional model of the object in real time. Experimental results show that this method only needs a single RGB-D camera, which is not only low cost and convenient to use, but also significantly improves the speed and accuracy of 3D reconstruction.

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REAL-TIME THREE-DIMENSIONAL RECONSTRUCTION FOR VOLUME-BASED SURGERY SIMULATIONS

Biomedical Engineering Applications Basis and Communications ◽

10.4015/s1016237208000799 ◽

2008 ◽

Vol 20 (04) ◽

pp. 205-218 ◽

Cited By ~ 4

Author(s):

Jyh-Fa Lee ◽

Ming-Shium Hsieh ◽

Chih-Wei Kuo ◽

Ming-Dar Tsai ◽

Ming Ma

Keyword(s):

3D Reconstruction ◽

Real Time ◽

Three Dimensional ◽

Reconstruction Method ◽

Three Dimensional Reconstruction ◽

Visual Responses ◽

Haptic Interactions ◽

Tissue Surfaces ◽

Dimensional Reconstruction ◽

Time Critical

This paper describes a three-dimensional reconstruction method to provide real-time visual responses for volume (constituted by tomographic slices) based surgery simulations. The proposed system uses dynamical data structures to record tissue triangles obtained from 3D reconstruction computation. Each tissue triangle in the structures can be modified or every structure can be deleted or allocated independently. Moreover, triangle reconstruction is optimized by only deleting or adding vertices from manipulated voxels that are classified as erosion (in which the voxels are changed from tissue to null) or generation (the voxels are changed from null to tissue). Therefore, by manipulating these structures, 3D reconstruction can be locally implemented for only manipulated voxels to achieve the highest efficiency without reconstructing tissue surfaces in the whole volume as general methods do. Three surgery simulation examples demonstrate that the proposed method can provide time-critical visual responses even under other time-consuming computations such as volume manipulations and haptic interactions.

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A Robust Real-Time 3D Reconstruction Method for Mixed Reality Telepresence

International Journal of Innovative Computing ◽

10.11113/ijic.v10n2.265 ◽

2020 ◽

Vol 10 (2) ◽

Author(s):

Fazliaty Edora Fadzli ◽

Ajune Wanis Ismail

Keyword(s):

3D Reconstruction ◽

Real Time ◽

Real World ◽

Mixed Reality ◽

Real Life ◽

Reconstruction Method ◽

Reconstruction Methods ◽

Virtual Element ◽

World Environment ◽

Full Body

Mixed Reality (MR) is a technology which enable to bring a virtual element into the real-world environment. MR intends to improve reality on the virtual world immerse onto real-world space. Occasionally the MR has been improved as the display technologies advanced progressively. In MR collaborative interface context, the local and remote user work together on collaborative task while sense the immersive environment in the cooperative application. User telepresence is an immersive telepresence, where the reconstruction of a human appears in a real-life. Up till now, producing full telepresence of the life-size human body may require a high transmission bandwidth of the internet. Therefore, this paper explores on a robust real-time 3D reconstruction method for MR telepresence. This paper discusses the previous works on the reconstruction method of a full-body human and the existing research works that have proposed the reconstruction methods for telepresence. Besides the 3D reconstruction method, this paper also enlightens our recent finding on the MR framework to transport a full-body human from a local location to a remote location. The MR telepresence will be discussed, as well as the robust 3D reconstruction method which has been implemented with user telepresence feature where the user experiences an accurate 3D representation of a remote person. The paper ends with the discussion and results, MR telepresence with robust 3D reconstruction method to execute user telepresence.

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Real-time 3D reconstruction method using massive multi-sensor data analysis and fusion

The Journal of Supercomputing ◽

10.1007/s11227-019-02747-3 ◽

2019 ◽

Vol 75 (6) ◽

pp. 3229-3248 ◽

Cited By ~ 1

Author(s):

Seoungjae Cho ◽

Kyungeun Cho

Keyword(s):

Data Analysis ◽

3D Reconstruction ◽

Real Time ◽

Sensor Data ◽

Reconstruction Method

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Research on 3D Reconstruction Method Based on Temporal Fourier Transform Profilometry

2020 2nd International Conference on Information Technology and Computer Application (ITCA) ◽

10.1109/itca52113.2020.00150 ◽

2020 ◽

Author(s):

Liao Min ◽

Luo weifeng

Keyword(s):

Fourier Transform ◽

3D Reconstruction ◽

Reconstruction Method ◽

Fourier Transform Profilometry

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3D RECONSTRUCTION OF BREAST CANCER FROM MAMMOGRAMS USING VOLUME RENDERING TECHNIQUES

Jurnal Teknologi ◽

10.11113/jt.v75.4978 ◽

2015 ◽

Vol 75 (2) ◽

Author(s):

Ho Wei Yong ◽

Abdullah Bade ◽

Rajesh Kumar Muniandy

Keyword(s):

Breast Cancer ◽

3D Reconstruction ◽

Computational Cost ◽

Reconstruction Method ◽

Cancer Model ◽

Volume Reconstruction ◽

The Past ◽

Breast Cancer Model ◽

Reconstruction Software ◽

To Come

Over the past thirty years, a number of researchers have investigated on 3D organ reconstruction from medical images and there are a few 3D reconstruction software available on the market. However, not many researcheshave focused on3D reconstruction of breast cancer’s tumours. Due to the method complexity, most 3D breast cancer’s tumours reconstruction were done based on MRI slices dataeven though mammogram is the current clinical practice for breast cancer screening. Therefore, this research will investigate the process of creating a method that will be able to reconstruct 3D breast cancer’s tumours from mammograms effectively. Several steps were proposed for this research which includes data acquisition, volume reconstruction, andvolume rendering. The expected output from this research is the 3D breast cancer’s tumours model that is generated from correctly registered mammograms. The main purpose of this research is to come up with a 3D reconstruction method that can produce good breast cancer model from mammograms while using minimal computational cost.

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