Multi-Drone 3D Building Reconstruction Method

In the recent decade, the rapid development of drone technologies has made many spatial problems easier to solve, including the problem of 3D reconstruction of large objects. A review of existing solutions has shown that most of the works lack the autonomy of drones because of nonscalable mapping techniques. This paper presents a method for centralized multi-drone 3D reconstruction, which allows performing a data capturing process autonomously and requires drones equipped only with an RGB camera. The essence of the method is a multiagent approach—the control center performs the workload distribution evenly and independently for all drones, allowing simultaneous flights without a high risk of collision. The center continuously receives RGB data from drones and performs each drone localization (using visual odometry estimations) and rough online mapping of the environment (using image descriptors for estimating the distance to the building). The method relies on a set of several user-defined parameters, which allows the tuning of the method for different task-specific requirements such as the number of drones, 3D model detalization, data capturing time, and energy consumption. By numerical experiments, it is shown that method parameters can be estimated by performing a set of computations requiring characteristics of drones and the building that are simple to obtain. Method performance was evaluated by an experiment with virtual building and emulated drone sensors. Experimental evaluation showed that the precision of the chosen algorithms for online localization and mapping is enough to perform simultaneous flights and the amount of captured RGB data is enough for further reconstruction.

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CROWD-SOURCED VISUAL DATA COLLECTION FOR MONITORING INDOOR CONSTRUCTION IN 3D

Proceedings of International Structural Engineering and Construction ◽

10.14455/isec.res.2018.15 ◽

2018 ◽

Vol 5 (1) ◽

Author(s):

Fouad Amer ◽

Mani Golparvar-Fard

Keyword(s):

Data Collection ◽

3D Reconstruction ◽

Structure From Motion ◽

Reconstruction Algorithm ◽

Point Clouds ◽

Reconstruction Method ◽

Visual Data ◽

Mapping Algorithm ◽

3D Point Clouds ◽

Localization And Mapping

Complete and accurate 3D monitoring of indoor construction progress using visual data is challenging. It requires (a) capturing a large number of overlapping images, which is time-consuming and labor-intensive to collect, and (b) processing using Structure from Motion (SfM) algorithms, which can be computationally expensive. To address these inefficiencies, this paper proposes a hybrid SfM-SLAM 3D reconstruction algorithm along with a decentralized data collection workflow to map indoor construction work locations in 3D and any desired frequency. The hybrid 3D reconstruction method is composed of a pipeline of Structure from Motion (SfM) coupled with Multi-View Stereo (MVS) to generate 3D point clouds and a SLAM (Simultaneous Localization and Mapping) algorithm to register the separately formed models together. Our SfM and SLAM pipelines are built on binary Oriented FAST and Rotated BRIEF (ORB) descriptors to tightly couple these two separate reconstruction workflows and enable fast computation. To elaborate the data capture workflow and validate the proposed method, a case study was conducted on a real-world construction site. Compared to state-of-the-art methods, our preliminary results show a decrease in both registration error and processing time, demonstrating the potential of using daily images captured by different trades coupled with weekly walkthrough videos captured by a field engineer for complete 3D visual monitoring of indoor construction operations.

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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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Research on Outdoor Garden Scene Reconstruction Based on PMVS Algorithm

Scientific Programming ◽

10.1155/2021/4491382 ◽

2021 ◽

Vol 2021 ◽

pp. 1-10

Author(s):

Wei He

Keyword(s):

3D Reconstruction ◽

Point Cloud ◽

Feature Matching ◽

Rapid Development ◽

Three Dimensional ◽

Reconstruction Method ◽

Feature Points ◽

Three Dimensional Reconstruction ◽

Dimensional Reconstruction ◽

Internet Of Things Technology

The three-dimensional reconstruction of outdoor landscape is of great significance for the construction of digital city. With the rapid development of big data and Internet of things technology, when using the traditional image-based 3D reconstruction method to restore the 3D information of objects in the image, there will be a large number of redundant points in the point cloud and the density of the point cloud is insufficient. Based on the analysis of the existing three-dimensional reconstruction technology, combined with the characteristics of outdoor garden scene, this paper gives the detection and extraction methods of relevant feature points and adopts feature matching and repairing the holes generated by point cloud meshing. By adopting the candidate strategy of feature points and adding the mesh subdivision processing method, an improved PMVS algorithm is proposed and the problem of sparse point cloud in 3D reconstruction is solved. Experimental results show that the proposed method not only effectively realizes the three-dimensional reconstruction of outdoor garden scene, but also improves the execution efficiency of the algorithm on the premise of ensuring the reconstruction effect.

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PERUBAHAN PERILAKU BERBELANJA DARI PASAR TRADISIONAL KE PASAR MODERN DI KOTA MANADO DIPANDANG DARI ASPEK SOSIOLOGI

Jurnal Ilmiah Al-Syir ah ◽

10.30984/as.v14i2.371 ◽

2017 ◽

Vol 14 (2) ◽

Author(s):

Marjam M. Pontorondo

Keyword(s):

Rapid Development ◽

Social Economy ◽

Modern Society ◽

Qualitative Approach ◽

Shopping Behavior ◽

Behavior Changes ◽

Social Changes ◽

Traditional Markets ◽

Traditional Market ◽

Time And Energy

This study about shopping behavior changes from traditional markets to modern market in the Manado city is viewed from the aspect of sociology. This study used a qualitative approach. The results showed that the shopping behavior of most citizens of Manado city has changed shopping habits in traditional markets into shopping habits in the modern market. Everyone in the economic measures based on efficiency considerations that revolve around efficiency of money and space also efficiency of time and energy. Before someone decides to shop, his views always consider the fourth aspect of it, and then decided to act. Thus the action is determined by the orientation to the person's environment that is tailored to the needs inherent in him. Then someone can act as he wishes. Most citizens of Manado city construct behavior of shopping habits in traditional markets into shopping habits in the modern market. The peoples leaving the characteristics of cooperation and confidence in social economy action trough activity in the traditional market began to fade, tend to behave consumerist, individualistic, laden competition, but innovation and creative. The pattern of this kind of action can be a collective action at the subjective macro level. This means that changes in individual behavior of Manado city residents at a certain level in line with the rapid development and progress of science and technology, will have implications on fundamental social changes in the structure of social behavior overall Manado city residents. Manado, will become a city inhabited by modern society with a consumption-oriented economic measures or commonly known as the consumerist society.

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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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