Human Face Fast-3D-Reconstruction from a Single Image

2012 ◽  
Vol 157-158 ◽  
pp. 1008-1011
Author(s):  
Hui Huang Zhao ◽  
Yao Nan Wang ◽  
Ya Qi Sun ◽  
Jian Zhen Chen
Keyword(s):  
Wavelet Transform ◽  
3D Reconstruction ◽  
Wavelet Packet ◽  
Three Dimensional ◽  
Reconstruction Algorithm ◽  
Shape From Shading ◽  
Wavelet Packet Transform ◽  
Reconstruction Method ◽  
Human Face ◽  
Single Image

Human face three-dimensional (3D) reconstruction is a challenging problem. In this paper, we propose a human face fast- 3D- reconstruction method based on image processing with a single image. Shape from shading (SFS) is chosen to reconstruct the human face. First, SFS theory is introduced. It has the advantage of fast 3D reconstruction and only need a single image. Secondly, because the noise will affect the 3D reconstruction result greatly, wavelet transform and wavelet packet transform are introduced and used in image denoising respectively. The experiment has shown that the method based on wavelet transform produces the best denoising result than wavelet packet transform. At last, a human face 3D reconstruction algorithm based on a single image is proposed. The experimental results show that a human face 3D model can be reconstructed in fast by proposed algorithm.

scholarly journals Three-Dimensional Reconstruction Method for Machined Surface Topography Based on Gray Gradient Constraints

2019 ◽  
Vol 9 (3) ◽  
pp. 591
Author(s):  
Wei-Chao Shi ◽  
Jian-Ming Zheng ◽  
Yan Li ◽  
Xu-Bo Li
Keyword(s):  
Surface Topography ◽  
Three Dimensional ◽  
Surface Characteristics ◽  
Reconstruction Algorithm ◽  
Shape From Shading ◽  
Reconstruction Method ◽  
Machined Surface ◽  
Reconstruction Methods ◽  
Product Function ◽  
Dimensional Reconstruction

In the modern engineering field, recovering the machined surface topography is important for studying mechanical product function and surface characteristics by using the shape from shading (SFS)-based reconstruction method. However, due to the limitations of many constraints and oversmoothing, the existing SFS-based reconstruction methods are not suitable for machined surface topography. This paper presents a new three-dimensional (3D) reconstruction method of machined surface topography. By combining the basic principle of SFS and the analytic method, the analytic model of a surface gradient is established using the gray gradient as a constraint condition. By efficiently solving the effect of quantization errors and ambiguity of the gray scale on reconstruction accuracy using a wavelet denoising algorithm and image processing technology, the reconstruction algorithm is implemented for machined surface topography. Experimental results on synthetic images and machined surface topography images show that the proposed algorithm can accurately and efficiently recover the 3D shape of machined surface topography.

scholarly journals A Single Image 3D Reconstruction Method Based on a Novel Monocular Vision System

Sensors ◽  
2020 ◽  
Vol 20 (24) ◽  
pp. 7045
Author(s):  
Fupei Wu ◽  
Shukai Zhu ◽  
Weilin Ye
Keyword(s):  
3D Reconstruction ◽  
Vision System ◽  
Incident Light ◽  
Three Dimensional ◽  
Ccd Camera ◽  
Monocular Vision ◽  
Reconstruction Method ◽  
Single Image ◽  
Color Distribution ◽  
3D Surface

Three-dimensional (3D) reconstruction and measurement are popular techniques in precision manufacturing processes. In this manuscript, a single image 3D reconstruction method is proposed based on a novel monocular vision system, which includes a three-level charge coupled device (3-CCD) camera and a ring structured multi-color light emitting diode (LED) illumination. Firstly, a procedure for the calibration of the illumination’s parameters, including LEDs’ mounted angles, distribution density and incident angles, is proposed. Secondly, the incident light information, the color distribution information and gray level information are extracted from the acquired image, and the 3D reconstruction model is built based on the camera imaging model. Thirdly, the surface height information of the detected object within the field of view is computed based on the built model. The proposed method aims at solving the uncertainty and the slow convergence issues arising in 3D surface topography reconstruction using current shape-from-shading (SFS) methods. Three-dimensional reconstruction experimental tests are carried out on convex, concave, angular surfaces and on a mobile subscriber identification module (SIM) card slot, showing relative errors less than 3.6%, respectively. Advantages of the proposed method include a reduced time for 3D surface reconstruction compared to other methods, demonstrating good suitability of the proposed method in reconstructing surface 3D morphology.

Application of Wavelet Transform in Signal Compression and Signal Recombination

2014 ◽  
Vol 986-987 ◽  
pp. 2056-2059
Author(s):  
Zhe Yuan Wang ◽  
Li Jiang
Keyword(s):  
Wavelet Transform ◽  
Wavelet Packet ◽  
Influence Factors ◽  
Wavelet Packet Transform ◽  
Signal Compression ◽  
Matlab Simulation ◽  
Paper Briefly ◽  
Simulation Experiments

This paper discusses the application of wavelet transform in signal compression and signal recombination detailedly. This paper briefly introduces the principle of wavelet transform in signal compression and signal recombination, this paper also introduces the wavelet MATLAB simulation experiments. This paper researches the differences the wavelet transform and wavelet packet transform in signal compression, this paper also briefly discusses the influence factors of signal compression.

Energy Distribution Analysis Regarding the Crack Size in a Rotating Shaft

2019 ◽  
Vol 24 (3) ◽  
pp. 418-425
Author(s):  
Cristina Cristina Castejon ◽  
Marıa Jesus Gomez ◽  
Juan Carlos Garcia-Prada ◽  
Eduardo Corral
Keyword(s):  
Wavelet Transform ◽  
Crack Detection ◽  
Wavelet Packet ◽  
Critical Role ◽  
Wavelet Packet Transform ◽  
Discrete Wavelet ◽  
Distribution Analysis ◽  
Rotating Shaft ◽  
Vibration Signals ◽  
Machine Monitoring

Maintenance is critical to avoid catastrophic failures in rotating machinery, and the detection of cracks plays a critical role because they can originate failures with costly processes of reparation, especially in shafts. Vibration signals are widely used in machine monitoring and fault diagnostics. The most critical issue in machine monitoring is the suitable selection of the vibration parameters that represent the condition of the machine. Discrete Wavelet Transform, and one of its recursive forms, called Wavelet Packet Transform, provide a high potential for pattern extraction. Several factors must be selected and taken into account in the Wavelet Transform application such as the level of decomposition, the suitable mother wavelet, and the level basis or features. In this work, the dynamic response of a shaft with different levels of crack is studied. The evolution of energy of the vibration signals obtained from the rotating shaft and the frequencies where maximum increments of energy appear with the crack are analyzed. The results allow the conclusion that changes in energies computed by means of the Wavelet Packet Transform can be successfully used for crack detection.

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

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.

A Simplified 3D Reconstruction Technique for Tomographic Particle Image Velocimetry

2013 ◽  
Vol 718-720 ◽  
pp. 2184-2190
Author(s):  
Bao Quan ◽  
Jiang Nan
Keyword(s):  
Particle Image Velocimetry ◽  
3D Reconstruction ◽  
Particle Image ◽  
Tomographic Reconstruction ◽  
Three Dimensional ◽  
Reconstruction Algorithm ◽  
Tomographic Particle Image Velocimetry ◽  
Image Velocimetry ◽  
3D Volume ◽  
Reconstruction Model

Tomographic particle image velocimetry (Tomo-PIV) is a newly developed technique for three-component three-dimensional (3C-3D) velocity measurement based on the tomographic reconstruction of a 3D volume light intensity field from multiple two-dimensional projections. A simplification of 3D tomographic reconstruction model, which reduced from a 3D volume with 2D images to a 2D slice with 1D lines, simplify this 3D reconstruction into a problem of 2D plane reconstruction by means of optical tomography, is applied in this paper . The principles and details of the tomographic algorithm are discussed, as well as the study of ART and MART reconstruction algorithm is carried out by means of computer-simulated image reconstruction procedure. The three-dimensional volume particle field is reconstructed by MART reconstruction algorithm base on the simplified 3D reconstruction model which made a high reconstruction quality Q=81.37% prove that the way of simplification by MART reconstruction is feasible, so it could be applied in reconstruction of 3D particle field in tomographic particle image velocimetry system.

Volume Measurement Method for Irregular Objects Based on Shape from Shading

2014 ◽  
Vol 494-495 ◽  
pp. 789-792
Author(s):  
Hong She Dang ◽  
Chu Jia Guo
Keyword(s):  
3D Reconstruction ◽  
Measurement Method ◽  
Convex Surface ◽  
Shape From Shading ◽  
Volume Measurement ◽  
Intensity Level ◽  
Reconstruction Method ◽  
Regular Shape ◽  
Image Acquisition System ◽  
3D Information

In this paper, we propose a volume measurement method for irregular objects. And three cameras were used in the image acquisition system. In order to reduce the intensity level and be more coincident with the 3D reconstruction method, a method called Histogram Acceleration has been used. Instead of using the regular shape from shading method, the relation between intensity and the missed 3D information was found. This method is valid within a certain error range. Its showed by experiment that this method has a good performance when dealing with objects with a smooth and convex surface.

scholarly journals Wavelet Transform for Signal Processing in Internet-of-Things (IoT)

2021 ◽  
Author(s):  
Indrakshi Dey ◽  
Shama Siddiqui
Keyword(s):  
Signal Processing ◽  
Wavelet Transform ◽  
Communication Networks ◽  
Wavelet Packet ◽  
Wavelet Packet Transform ◽  
Wireless Communication Networks ◽  
Impact Noise ◽  
Sensor Signals ◽  
Processing Steps ◽  
Primary Contribution

The primary contribution of this chapter is to provide an overview of different denoising methods used for signal processing in IoT networks from the perspectives of physical layer in the network. The chapter starts with the introduction to different kinds of noise that can be encountered in any kind of wireless communication networks, different kinds of wavelet transform and wavelet packet transform methods that can be used for denoising sensor signals in IoT networks and the different processing steps that are needed to be followed to accomplish wavelet packet transform for the sensor signals. Finally, a universal framework based on energy correlation analysis has been presented for denoising sensor signals in IoT networks, and such a framework can achieve considerable improvement in denoising performance reducing the effective noise correlation coefficient to 0.00001 or lower. Moreover, this method is found to be equally effective for Gaussian or impact noise or both.

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