scholarly journals Automated 3D Scenes Reconstruction Using Multiple Stereo Pairs from Portable Four-Camera Photographic Measurement System

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Qi Peng ◽  
Lifen Tu ◽  
Kaibing Zhang ◽  
Sidong Zhong
Keyword(s):  
3D Reconstruction ◽  
Measurement System ◽  
3D Model ◽  
Low Cost ◽  
Reconstruction Method ◽  
Feature Points ◽  
Point Matching ◽  
Mogao Grottoes ◽  
Feature Point Matching ◽  
3D Scene

An effective automatic 3D reconstruction method using a portable four-camera photographic measurement system (PFCPMS) is proposed. By taking advantage of the complementary stereo information from four cameras, a fast and highly accurate feature point matching algorithm is developed for 3D reconstruction. Specifically, we first utilize a projection method to obtain a large number of dense feature points. And then a reduction and clustering treatment is applied to simplify the Delaunay triangulation process and reconstruct a 3D model for each scene. In addition, a 3D model stitching approach is proposed to further improve the performance of the limited field-of-view for image-based method. The experimental results tested on the 172 cave in Mogao Grottoes indicate that the proposed method is effective to reconstruct a 3D scene with a low-cost four-camera photographic measurement system.

scholarly journals AN AUTOMATIC 3D RECONSTRUCTION METHOD BASED ON MULTI-VIEW STEREO VISION FOR THE MOGAO GROTTOES

2015 ◽  
Vol XL-4/W5 ◽  
pp. 171-176 ◽  
Author(s):  
J. Xiong ◽  
S. Zhong ◽  
L. Zheng
Keyword(s):  
3D Reconstruction ◽  
Stereo Vision ◽  
Measurement System ◽  
Stereo Matching ◽  
Three Dimensional ◽  
Texture Mapping ◽  
Reconstruction Method ◽  
Epipolar Constraint ◽  
Mogao Grottoes ◽  
Binocular Stereo

This paper presents an automatic three-dimensional reconstruction method based on multi-view stereo vision for the Mogao Grottoes. 3D digitization technique has been used in cultural heritage conservation and replication over the past decade, especially the methods based on binocular stereo vision. However, mismatched points are inevitable in traditional binocular stereo matching due to repeatable or similar features of binocular images. In order to reduce the probability of mismatching greatly and improve the measure precision, a portable four-camera photographic measurement system is used for 3D modelling of a scene. Four cameras of the measurement system form six binocular systems with baselines of different lengths to add extra matching constraints and offer multiple measurements. Matching error based on epipolar constraint is introduced to remove the mismatched points. Finally, an accurate point cloud can be generated by multi-images matching and sub-pixel interpolation. Delaunay triangulation and texture mapping are performed to obtain the 3D model of a scene. The method has been tested on 3D reconstruction several scenes of the Mogao Grottoes and good results verify the effectiveness of the method.

scholarly journals Scene Wireframes Sketching for Drones

Proceedings ◽  
2018 ◽  
Vol 2 (18) ◽  
pp. 1193
Author(s):  
Roi Santos ◽  
Xose Pardo ◽  
Xose Fdez-Vidal
Keyword(s):  
State Of The Art ◽  
Point Clouds ◽  
Outdoor Environment ◽  
Point Matching ◽  
3D Point Clouds ◽  
Complementary Approach ◽  
Straight Line ◽  
Scene Representation ◽  
Feature Point Matching ◽  
3D Scene

The increasing use of autonomous UAVs inside buildings and around human-made structures demands new accurate and comprehensive representation of their operation environments. Most of the 3D scene abstraction methods use invariant feature point matching, nevertheless some sparse 3D point clouds do not concisely represent the structure of the environment. Likewise, line clouds constructed by short and redundant segments with inaccurate directions limit the understanding of scenes as those that include environments with poor texture, or whose texture resembles a repetitive pattern. The presented approach is based on observation and representation models using the straight line segments, whose resemble the limits of an urban indoor or outdoor environment. The goal of the work is to get a full method based on the matching of lines that provides a complementary approach to state-of-the-art methods when facing 3D scene representation of poor texture environments for future autonomous UAV.

scholarly journals A Poisson Equation-Based Method for 3D Reconstruction of Animated Images

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Ziang Lei
Keyword(s):  
3D Reconstruction ◽  
Real Time ◽  
Large Scale ◽  
Least Square ◽  
Reconstruction Method ◽  
Feature Points ◽  
Computing Power ◽  
To Come ◽  
Point Detection ◽  
Considerable Period

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.

A New Method for Feature Point Matching: Inner and Exterior Product

2011 ◽  
Vol 48-49 ◽  
pp. 79-83
Author(s):  
Xu Guang Wang ◽  
Li Jun Lin ◽  
Hai Yan Cheng
Keyword(s):  
Feature Point ◽  
Feature Descriptor ◽  
Feature Points ◽  
Correlation Measure ◽  
Exterior Product ◽  
Illumination Change ◽  
Point Matching ◽  
Feature Point Matching ◽  
Estimate Precision ◽  
Better Than

In this paper, a novel feature descriptor called gradient correlation descriptor (GCD) is proposed. The GCD descriptor uses the gradient correlation measure defined by the inner and exterior product to characterize the gradient distributions in neighborhoods of feature points, and it has the following advantages: Its construction is very simple because of only the inner and exterior product operations are used; Its distinctive performance is better than the region-based SIFT descriptors since the gradient correlation measure can effectively characterize the gradient distributions in neighborhoods of feature points; In the gradient correlation measure the use of gradient mean makes it is not sensitive to the estimate precision of main orientation of feature point, and thus can provide a better stabilization to image rotation; The gradient correlation measure makes it also has very good adaptability to image affine transform, image blur, JPEG compression as well as illumination change.

A 3D Reconstruction Method Based on Binocular View Geometry

2010 ◽  
Vol 33 ◽  
pp. 299-303
Author(s):  
Zhong Yan Liu ◽  
Guo Quan Wang ◽  
Dong Ping Wang
Keyword(s):  
3D Reconstruction ◽  
Three Dimensional ◽  
Reconstruction Method ◽  
Feature Points ◽  
Imaging Model ◽  
Extrinsic Parameters ◽  
Image Acquisition System ◽  
Rearview Mirror ◽  
3D Information ◽  
Intrinsic And Extrinsic Parameters

A method was proposed to gain three-dimensional (3D) reconstruction based on binocular view geometry. Images used to calibrate cameras and reconstruct car’s rearview mirror by image acquisition system, by calibration image, a camera's intrinsic and extrinsic parameters, projective and fundamental matrixes were drawn by Matlab7.1;the collected rearview mirror images is pretreated to draw refined laser, extracted feature points, find the very appropriate match points by epipolar geometry principle; according to the camera imaging model to calculate the coordinates of space points, display point cloud, fitting space points to reconstruct car’s rearview mirror; experimental results show this method can better restore the car’s rearview mirror of 3D information.

Image Mosaics Algorithm Combined Feature Point Matching with Transformation Parameters

2013 ◽  
Vol 380-384 ◽  
pp. 4136-4139
Author(s):  
Peng Rui Qiu ◽  
Ying Liang ◽  
Hui Rong
Keyword(s):  
Projective Transformation ◽  
Feature Point ◽  
Image Mosaic ◽  
Feature Points ◽  
Geometric Information ◽  
Point Matching ◽  
Feature Point Matching ◽  
Transformation Parameters ◽  
Relationship Of ◽  
The Relationship

To solve the problem of the large amount of calculation, poor robustness and do not well in image mosaic of images who are in different scales in the traditional image mosaic method ,the article arise a mosaic algorithm of different scales images registration and adaptive. Through feature point matching and automatically recognizing of transform geometric parameters between images,It achieves the match and mosaic of different scale and rotated images. First, using SIFT to extract the feature points of the images and matching feature points according to the principal of mutual information maximum. Then based on the geometric information of the matching pairs, automatically recognize the relationship of transformation parameters. In the end, obtain the projective transformation and achieve the image stable mosaic.

scholarly journals A Study of 3D Digitisation Modalities for Crime Scene Investigation

2021 ◽  
Vol 1 (2) ◽  
pp. 56-85
Author(s):  
George Galanakis ◽  
Xenophon Zabulis ◽  
Theodore Evdaimon ◽  
Sven-Eric Fikenscher ◽  
Sebastian Allertseder ◽  
...  
Keyword(s):  
3D Reconstruction ◽  
Low Cost ◽  
Crime Scene ◽  
Reconstruction Method ◽  
Crime Scene Investigation ◽  
The Public ◽  
Wide Range ◽  
Time Availability ◽  
Scene Investigation ◽  
3D Digitisation

A valuable aspect during crime scene investigation is the digital documentation of the scene. Traditional means of documentation include photography and in situ measurements from experts for further analysis. Although 3D reconstruction of pertinent scenes has already been explored as a complementary tool in investigation pipelines, such technology is considered unfamiliar and not yet widely adopted. This is explained by the expensive and specialised digitisation equipment that is available so far. However, the emergence of high-precision but low-cost devices capable of scanning scenes or objects in 3D has been proven as a reliable alternative to their counterparts. This paper summarises and analyses the state-of-the-art technologies in scene documentation using 3D digitisation and assesses the usefulness in typical police-related situations and the forensics domain in general. We present the methodology for acquiring data for 3D reconstruction of various types of scenes. Emphasis is placed on the applicability of each technique in a wide range of situations, ranging in type and size. The application of each reconstruction method is considered in this context and compared with respect to additional constraints, such as time availability and simplicity of operation of the corresponding scanning modality. To further support our findings, we release a multi-modal dataset obtained from a hypothetical indoor crime scene to the public.

Unusual Event Detection using Mean Feature Point Matching Algorithm

2016 ◽  
Vol 6 (4) ◽  
pp. 1595 ◽  
Author(s):  
Chitra Hegde ◽  
Shakti Singh Chundawat ◽  
Divya S N
Keyword(s):  
Input Image ◽  
Feature Point ◽  
Experimental Result ◽  
Feature Points ◽  
Surveillance Video ◽  
Point Matching ◽  
Public And Private ◽  
Unusual Event ◽  
Speeded Up Robust Features ◽  
Feature Point Matching

Analysis and detection of unusual events in public and private surveillance system is a complex task. Detecting unusual events in surveillance video requires the appropriate definition of similarity between events. The key goal of the proposed system is to detect behaviours or actions that can be considered as anomalies. Since suspicious events differ from domain to domain, it remains a challenge to detect those events in major domains such as airport, super malls, educational institutions etc. The proposed Mean Feature Point Matching (MFPM) algorithm is used for detecting unusual events. The Speeded-Up Robust Features (SURF) method is used for feature extraction. The MFPM algorithm compares the feature points of the input image with the mean feature points of trained dataset. The experimental result shows that the proposed system is efficient and accurate for wide variety of surveillance videos.

scholarly journals Improved Parallax Image Stitching Algorithm Based on Feature Block

Symmetry ◽  
2019 ◽  
Vol 11 (3) ◽  
pp. 348 ◽  
Author(s):  
Huaitao Shi ◽  
Lei Guo ◽  
Shuai Tan ◽  
Gang Li ◽  
Jie Sun
Keyword(s):  
Feature Matching ◽  
Computational Cost ◽  
Reference Image ◽  
Image Stitching ◽  
Feature Points ◽  
Shape Distortion ◽  
Scale Invariant ◽  
Point Matching ◽  
Feature Point Matching ◽  
Scale Invariant Feature

Image stitching aims at generating high-quality panoramas with the lowest computational cost. In this paper, we present an improved parallax image-stitching algorithm using feature blocks (PIFB), which achieves a more accurate alignment and faster calculation speed. First, each image is divided into feature blocks using an improved fuzzy C-Means (FCM) algorithm, and the characteristic descriptor of each feature block is extracted using scale invariant feature transform (SIFT). The feature matching block of the reference image and the target image are matched and then determined, and the image is pre-registered using the homography calculated by the feature points in the feature block. Finally, the overlapping area is optimized to avoid ghosting and shape distortion. The improved algorithm considering pre-blocking and block stitching effectively reduced the iterative process of feature point matching and homography calculation. More importantly, the problem that the calculated homography matrix was not global has been solved. Ghosting and shape warping are significantly eliminated by re-optimizing the overlap of the image. The performance of the proposed approach is demonstrated using several challenging cases.

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