3D reconstruction of human head based on consumer RGB-D sensors

2020 ◽  
pp. 2050061
Author(s):  
Zihan Liu ◽  
Guanghong Gong ◽  
Ni Li ◽  
Zihao Yu
Keyword(s):  
3D Reconstruction ◽  
Low Cost ◽  
Three Dimensional ◽  
Human Head ◽  
Point Clouds ◽  
Microsoft Kinect ◽  
Head Model ◽  
Registration Method ◽  
Three Dimensional Modeling ◽  
Texture Generation

Three-dimensional (3D) reconstruction of a human head with high precision has promising applications in scientific research, product design and other fields. However, it still faces resistance from two factors. One is inaccurate registration caused by symmetrical distribution of head feature points, and the other is economic burden due to high-accuracy sensors. Research on 3D reconstruction with portable consumer RGB-D sensors such as the Microsoft Kinect has been highlighted in recent years. Based on our multi-Kinect system, a precise and low-cost three-dimensional modeling method and its system implementation are introduced in this paper. A registration method for multi-source point clouds is provided, which can reduce the fusion differences and reconstruct the head model accurately. In addition, a template-based texture generation algorithm is presented to generate a fine texture. The comparison and analysis of our experiments show that our method can reconstruct a head model in an acceptable time with less memory and better effect.

scholarly journals Estimating tree stem diameters and volume from smartphone photogrammetric point clouds

2019 ◽  
Vol 93 (3) ◽  
pp. 411-429 ◽  
Author(s):  
Maria Immacolata Marzulli ◽  
Pasi Raumonen ◽  
Roberto Greco ◽  
Manuela Persia ◽  
Patrizia Tartarino
Keyword(s):  
Low Cost ◽  
Three Dimensional ◽  
Laser Scanner ◽  
Point Clouds ◽  
Stem Volume ◽  
Forest Plot ◽  
3D Point Clouds ◽  
Dense Point ◽  
Minimum Number ◽  
Scale Point

Abstract Methods for the three-dimensional (3D) reconstruction of forest trees have been suggested for data from active and passive sensors. Laser scanner technologies have become popular in the last few years, despite their high costs. Since the improvements in photogrammetric algorithms (e.g. structure from motion—SfM), photographs have become a new low-cost source of 3D point clouds. In this study, we use images captured by a smartphone camera to calculate dense point clouds of a forest plot using SfM. Eighteen point clouds were produced by changing the densification parameters (Image scale, Point density, Minimum number of matches) in order to investigate their influence on the quality of the point clouds produced. In order to estimate diameter at breast height (d.b.h.) and stem volumes, we developed an automatic method that extracts the stems from the point cloud and then models them with cylinders. The results show that Image scale is the most influential parameter in terms of identifying and extracting trees from the point clouds. The best performance with cylinder modelling from point clouds compared to field data had an RMSE of 1.9 cm and 0.094 m3, for d.b.h. and volume, respectively. Thus, for forest management and planning purposes, it is possible to use our photogrammetric and modelling methods to measure d.b.h., stem volume and possibly other forest inventory metrics, rapidly and without felling trees. The proposed methodology significantly reduces working time in the field, using ‘non-professional’ instruments and automating estimates of dendrometric parameters.

scholarly journals ACCURACY ASSESSMENT OF UNDERWATER PHOTOGRAMMETRIC THREE DIMENSIONAL MODELLING FOR CORAL REEFS

2016 ◽  
Vol XLI-B5 ◽  
pp. 821-828 ◽  
Author(s):  
T. Guo ◽  
A. Capra ◽  
M. Troyer ◽  
A. Gruen ◽  
A. J. Brooks ◽  
...  
Keyword(s):  
Coral Cover ◽  
Accuracy Assessment ◽  
Low Cost ◽  
Three Dimensional ◽  
Point Clouds ◽  
3D Modelling ◽  
Relative Accuracy ◽  
3D Point Clouds ◽  
The Individual ◽  
Working Distance

Recent advances in automation of photogrammetric 3D modelling software packages have stimulated interest in reconstructing highly accurate 3D object geometry in unconventional environments such as underwater utilizing simple and low-cost camera systems. The accuracy of underwater 3D modelling is affected by more parameters than in single media cases. This study is part of a larger project on 3D measurements of temporal change of coral cover in tropical waters. It compares the accuracies of 3D point clouds generated by using images acquired from a system camera mounted in an underwater housing and the popular GoPro cameras respectively. A precisely measured calibration frame was placed in the target scene in order to provide accurate control information and also quantify the errors of the modelling procedure. In addition, several objects (cinder blocks) with various shapes were arranged in the air and underwater and 3D point clouds were generated by automated image matching. These were further used to examine the relative accuracy of the point cloud generation by comparing the point clouds of the individual objects with the objects measured by the system camera in air (the best possible values). Given a working distance of about 1.5 m, the GoPro camera can achieve a relative accuracy of 1.3 mm in air and 2.0 mm in water. The system camera achieved an accuracy of 1.8 mm in water, which meets our requirements for coral measurement in this system.

scholarly journals Structured-Light Based 3D Reconstruction System for Cultural Relic Packaging

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 2981 ◽  
Author(s):  
Limei Song ◽  
Xinyao Li ◽  
Yan-gang Yang ◽  
Xinjun Zhu ◽  
Qinghua Guo ◽  
...  
Keyword(s):  
3D Reconstruction ◽  
High Efficiency ◽  
Low Cost ◽  
Structured Light ◽  
Three Dimensional ◽  
Cloud Data ◽  
Dimensional Measurement ◽  
Cost System ◽  
Three Dimensional Measurement ◽  
Cultural Relics

The non-contact three-dimensional measurement and reconstruction techniques have played a significant role in the packaging and transportation of precious cultural relics. This paper develops a structured light based three-dimensional measurement system, with a low-cost for cultural relics packaging. The structured light based system performs rapid measurements and generates 3D point cloud data, which is then denoised, registered and merged to achieve accurate 3D reconstruction for cultural relics. The multi-frequency heterodyne method and the method in this paper are compared. It is shown that the relative accuracy of the proposed low-cost system can reach a level of 1/1000. The high efficiency of the system is demonstrated through experimental results.

Study on laser scanning three-dimensional modeling of human head

2005 ◽  
Author(s):  
Tao Wang ◽  
Jianquan Yao ◽  
Ling Guo ◽  
Binjing Cai ◽  
Yang Lu ◽  
...  
Keyword(s):  
Laser Scanning ◽  
Three Dimensional ◽  
Human Head ◽  
Three Dimensional Modeling ◽  
Dimensional Modeling

scholarly journals Quantification of Extent, Density, and Status of Aquatic Reed Beds Using Point Clouds Derived from UAV–RGB Imagery

2018 ◽  
Vol 10 (12) ◽  
pp. 1869 ◽  
Author(s):  
Nicolás Corti Meneses ◽  
Florian Brunner ◽  
Simon Baier ◽  
Juergen Geist ◽  
Thomas Schneider
Keyword(s):  
Cross Sections ◽  
Vegetation Index ◽  
Low Cost ◽  
Three Dimensional ◽  
Field Measurements ◽  
Point Clouds ◽  
Conservation Strategies ◽  
Reed Beds ◽  
Combining Data ◽  
Reed Bed

Quantification of reed coverage and vegetation status is fundamental for monitoring and developing lake conservation strategies. The applicability of Unmanned Aerial Vehicles (UAV) three-dimensional data (point clouds) for status evaluation was investigated. This study focused on mapping extent, density, and vegetation status of aquatic reed beds. Point clouds were calculated with Structure from Motion (SfM) algorithms in aerial imagery recorded with Rotary Wing (RW) and Fixed Wing (FW) UAV. Extent was quantified by measuring the surface between frontline and shoreline. Density classification was based on point geometry (height and height variance) in point clouds. Spectral information per point was used for calculating a vegetation index and was used as indicator for vegetation vitality. Status was achieved by combining data on density, vitality, and frontline shape outputs. Field observations in areas of interest (AOI) and optical imagery were used for reference and validation purposes. A root mean square error (RMSE) of 1.58 m to 3.62 m for cross sections from field measurements and classification was achieved for extent map. The overall accuracy (OA) acquired for density classification was 88.6% (Kappa = 0.8). The OA for status classification of 83.3% (Kappa = 0.7) was reached by comparison with field measurements complemented by secondary Red, Green, Blue (RGB) data visual assessments. The research shows that complex transitional zones (water–vegetation–land) can be assessed and support the suitability of the applied method providing new strategies for monitoring aquatic reed bed using low-cost UAV imagery.

scholarly journals A Three-Dimensional Computational Human Head Model That Captures Live Human Brain Dynamics

2017 ◽  
Vol 34 (13) ◽  
pp. 2154-2166 ◽  
Author(s):  
Shailesh Ganpule ◽  
Nitin P. Daphalapurkar ◽  
Kaliat T. Ramesh ◽  
Andrew K. Knutsen ◽  
Dzung L. Pham ◽  
...  
Keyword(s):  
Human Brain ◽  
Three Dimensional ◽  
Human Head ◽  
Brain Dynamics ◽  
Head Model ◽  
Human Head Model

scholarly journals Workflow: From photo-based 3-D reconstruction of remotely piloted aircraft images to a 3-D geological model

Geosphere ◽  
2019 ◽  
Vol 15 (4) ◽  
pp. 1393-1408 ◽  
Author(s):  
Reuben J. Hansman ◽  
Uwe Ring
Keyword(s):  
Remote Sensing ◽  
United Arab Emirates ◽  
Low Cost ◽  
Three Dimensional ◽  
Point Clouds ◽  
Geological Mapping ◽  
Geological Model ◽  
Geological Processes ◽  
Aerial Imaging ◽  
Remotely Piloted Aircraft

AbstractGeological field mapping is a vital first step in understanding geological processes. During the 20th century, mapping was revolutionized through advances in remote sensing technology. With the recent availability of low-cost remotely piloted aircraft (RPA), field geologists now routinely carry out aerial imaging without the need to use satellite, helicopter, or airplane systems. RPA photographs are processed by photo-based three-dimensional (3-D) reconstruction software, which uses structure-from-motion and multi-view stereo algorithms to create an ultra-high-resolution, 3-D point cloud of a region or target outcrop. These point clouds are analyzed to extract the orientation of geological structures and strata, and are also used to create digital elevation models and photorealistic 3-D models. However, this technique has only recently been used for structural mapping. Here, we outline a workflow starting with RPA data acquisition, followed by photo-based 3-D reconstruction, and ending with a 3-D geological model. The Jabal Hafit anticline in the United Arab Emirates was selected to demonstrate this workflow. At this anticline, outcrop exposure is excellent and the terrain is challenging to navigate due to areas of high relief. This makes for an ideal RPA mapping site and provides a good indication of how practical this method may be for the field geologist. Results confirm that RPA photo-based 3-D reconstruction mapping is an accurate and cost-efficient remote sensing method for geological mapping.

scholarly journals Finite-element analysis of microwave scattering from a three-dimensional human head model for brain stroke detection

2018 ◽  
Vol 5 (7) ◽  
pp. 180319
Author(s):  
Awais Munawar Qureshi ◽  
Zartasha Mustansar ◽  
Samah Mustafa
Keyword(s):  
Finite Element ◽  
Dielectric Properties ◽  
Electric Field ◽  
Three Dimensional ◽  
Human Head ◽  
Head Model ◽  
Different Types ◽  
Brain Stroke ◽  
Human Head Model ◽  
Brain Stroke Detection

In this paper, a detailed analysis of microwave (MW) scattering from a three-dimensional (3D) anthropomorphic human head model is presented. It is the first time that the finite-element method (FEM) has been deployed to study the MW scattering phenomenon of a 3D realistic head model for brain stroke detection. A major contribution of this paper is to add anatomically more realistic details to the human head model compared with the literature available to date. Using the MRI database, a 3D numerical head model was developed and segmented into 21 different types through a novel tissue-mapping scheme and a mixed-model approach. The heterogeneous and frequency-dispersive dielectric properties were assigned to brain tissues using the same mapping technique. To mimic the simulation set-up, an eight-elements antenna array around the head model was designed using dipole antennae. Two types of brain stroke (haemorrhagic and ischaemic) at various locations inside the head model were then analysed for possible detection and classification. The transmitted and backscattered signals were calculated by finding out the solution of the Helmholtz wave equation in the frequency domain using the FEM. FE mesh convergence analysis for electric field values and comparison between different types of iterative solver were also performed to obtain error-free results in minimal computational time. At the end, specific absorption rate analysis was conducted to examine the ionization effects of MW signals to a 3D human head model. Through computer simulations, it is foreseen that MW imaging may efficiently be exploited to locate and differentiate two types of brain stroke by detecting abnormal tissues’ dielectric properties. A significant contrast between electric field values of the normal and stroke-affected brain tissues was observed at the stroke location. This is a step towards generating MW scattering information for the development of an efficient image reconstruction algorithm.

Conceptual Three-Dimensional Modeling Using Intuitive Gesture-Based Midair Three-Dimensional Sketching Technique

2018 ◽  
Vol 18 (4) ◽  
Author(s):  
Jinmiao Huang ◽  
Rahul Rai
Keyword(s):  
User Study ◽  
Low Cost ◽  
Three Dimensional ◽  
3D Models ◽  
Interaction Technique ◽  
Three Dimensional Modeling ◽  
Study Results ◽  
Novice Users ◽  
Technical Solutions ◽  
3D Shapes

We introduce an intuitive gesture-based interaction technique for creating and manipulating simple three-dimensional (3D) shapes. Specifically, the developed interface utilizes low-cost depth camera to capture user's hand gesture as the input, maps different gestures to system commands and generates 3D models from midair 3D sketches (as opposed to traditional two-dimensional (2D) sketches). Our primary contribution is in the development of an intuitive gesture-based interface that enables novice users to rapidly construct conceptual 3D models. Our development extends current works by proposing both design and technical solutions to the challenges of the gestural modeling interface for conceptual 3D shapes. The preliminary user study results suggest that the developed framework is intuitive to use and able to create a variety of 3D conceptual models.

scholarly journals USE OF ASSISTED PHOTOGRAMMETRY FOR INDOOR AND OUTDOOR NAVIGATION PURPOSES

2015 ◽  
Vol XL-4/W5 ◽  
pp. 113-118 ◽  
Author(s):  
D. Pagliari ◽  
N. E. Cazzaniga ◽  
L. Pinto
Keyword(s):  
Urban Areas ◽  
Low Cost ◽  
Point Clouds ◽  
Satellite System ◽  
Indoor Navigation ◽  
Microsoft Kinect ◽  
Textured Surfaces ◽  
Navigation Problem ◽  
Additional Information ◽  
Outdoor Navigation

Nowadays, devices and applications that require navigation solutions are continuously growing. For instance, consider the increasing demand of mapping information or the development of applications based on users’ location. In some case it could be sufficient an approximate solution (e.g. at room level), but in the large amount of cases a better solution is required. <br><br> The navigation problem has been solved from a long time using Global Navigation Satellite System (GNSS). However, it can be unless in obstructed areas, such as in urban areas or inside buildings. An interesting low cost solution is photogrammetry, assisted using additional information to scale the photogrammetric problem and recovering a solution also in critical situation for image-based methods (e.g. poor textured surfaces). In this paper, the use of assisted photogrammetry has been tested for both outdoor and indoor scenarios. Outdoor navigation problem has been faced developing a positioning system with Ground Control Points extracted from urban maps as constrain and tie points automatically extracted from the images acquired during the survey. The proposed approach has been tested under different scenarios, recovering the followed trajectory with an accuracy of 0.20 m. <br><br> For indoor navigation a solution has been thought to integrate the data delivered by Microsoft Kinect, by identifying interesting features on the RGB images and re-projecting them on the point clouds generated from the delivered depth maps. Then, these points have been used to estimate the rotation matrix between subsequent point clouds and, consequently, to recover the trajectory with few centimeters of error.

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