scholarly journals A Unified Framework for Depth Prediction from a Single Image and Binocular Stereo Matching

2020 ◽  
Vol 12 (3) ◽  
pp. 588
Author(s):  
Wei Chen ◽  
Xin Luo ◽  
Zhengfa Liang ◽  
Chen Li ◽  
Mingfei Wu ◽  
...  
Keyword(s):  
Stereo Matching ◽  
Depth Information ◽  
Training Procedure ◽  
Single Image ◽  
Unified Framework ◽  
Depth Prediction ◽  
Training Samples ◽  
Binocular Stereo ◽  
Left Image ◽  
The Right

Depth information has long been an important issue in computer vision. The methods for this can be categorized into (1) depth prediction from a single image and (2) binocular stereo matching. However, these two methods are generally regarded as separate tasks, which are accomplished in different network architectures when using deep learning-based methods. This study argues that these two tasks can be achieved using only one network with the same weights. We modify existing networks for stereo matching to perform the two tasks. We first enable the network capable of accepting both a single image and an image pair by duplicating the left image when the right image is absent. Then, we introduce a training procedure that alternatively selects training samples of depth prediction from a single image and binocular stereo matching. In this manner, the trained network can perform both tasks and single-image depth prediction even benefits from stereo matching to achieve better performance. Experimental results on KITTI raw dataset show that our model achieves state-of-the-art performances for accomplishing depth prediction from a single image and binocular stereo matching in the same architecture.

High-Precision 3D Modeling Method Based on Terrestrial Image Sequences for Alpine-Gorge Area

2012 ◽  
Vol 182-183 ◽  
pp. 1270-1275 ◽  
Author(s):  
Bo Su ◽  
Hao Li ◽  
Ya Qin Wang ◽  
Biao Yang
Keyword(s):  
Stereo Matching ◽  
Three Dimensional ◽  
Digital Camera ◽  
Image Sequences ◽  
Three Dimensional Modeling ◽  
Modeling Process ◽  
Dimensional Modeling ◽  
Left Image ◽  
The Right ◽  
Seed Points

The traditional measurement methods cannot adapt to the arduous topography of alpine-gorge area. Aiming at the topographical features of alpine-gorge area, we will introduce a general terrestrial method of multi-baseline photogrammetry basing on digital camera here, and then the paper mainly studies the metrization method of common digital camera and matching method of the digital image sequences of alpine-gorge area. Through the metrization of common digital camera, the efficiency of terrain data collection will increase in the alpine-gorge area, and the requirements of operations on the image control and algorithm will reduce. The combination of seed points and multiple constraints in multi-baseline stereo matching will help to solve many problems, such as shading, severe distortion between the left image and the right one, and the inconformity of scale. The modeling process stated above is quite fast and highly precise, and the three-dimensional modeling experiments show that the relative accuracy can reach from 1 / 8000 to 1 / 12000.

scholarly journals Panoramic Stereo Imaging of a Bionic Compound-Eye Based on Binocular Vision

Sensors ◽  
2021 ◽  
Vol 21 (6) ◽  
pp. 1944
Author(s):  
Xinhua Wang ◽  
Dayu Li ◽  
Guang Zhang
Keyword(s):  
Real Time ◽  
Stereo Vision ◽  
Optimization Design ◽  
Stereo Matching ◽  
Depth Information ◽  
Stereo Imaging ◽  
Design Scheme ◽  
Panoramic Imaging ◽  
Binocular Stereo Vision ◽  
Binocular Stereo

With the rapid development of the virtual reality industry, one of the bottlenecks is the scarcity of video resources. How to capture high-definition panoramic video with depth information and real-time stereo display has become a key technical problem to be solved. In this paper, the optical optimization design scheme of panoramic imaging based on binocular stereo vision is proposed. Combined with the real-time processing algorithm of multi detector mosaic panoramic stereo imaging image, a panoramic stereo real-time imaging system is developed. Firstly, the optical optimization design scheme of panoramic imaging based on binocular stereo vision is proposed, and the space coordinate calibration platform of ultra-high precision panoramic camera based on theodolite angle compensation function is constructed. The projection matrix of adjacent cameras is obtained by solving the imaging principle of binocular stereo vision. Then, a real-time registration algorithm of multi-detector mosaic image and Lucas-Kanade optical flow method based on image segmentation are proposed to realize stereo matching and depth information estimation of panoramic imaging, and the estimation results are analyzed effectively. Experimental results show that the stereo matching time of panoramic imaging is 30 ms, the registration accuracy is 0.1 pixel, the edge information of depth map is clearer, and it can meet the imaging requirements of different lighting conditions.

scholarly journals A Fast Stereo Matching Network with Multi-Cross Attention

Sensors ◽  
2021 ◽  
Vol 21 (18) ◽  
pp. 6016
Author(s):  
Ming Wei ◽  
Ming Zhu ◽  
Yi Wu ◽  
Jiaqi Sun ◽  
Jiarong Wang ◽  
...  
Keyword(s):  
Deep Learning ◽  
Stereo Matching ◽  
Disparity Estimation ◽  
Stereo Image ◽  
Matching Network ◽  
Low Resolution ◽  
Attention Model ◽  
Binocular Stereo ◽  
End To End ◽  
Left Image

Stereo matching networks based on deep learning are widely developed and can obtain excellent disparity estimation. We present a new end-to-end fast deep learning stereo matching network in this work that aims to determine the corresponding disparity from two stereo image pairs. We extract the characteristics of the low-resolution feature images using the stacked hourglass structure feature extractor and build a multi-level detailed cost volume. We also use the edge of the left image to guide disparity optimization and sub-sample with the low-resolution data, ensuring excellent accuracy and speed at the same time. Furthermore, we design a multi-cross attention model for binocular stereo matching to improve the matching accuracy and achieve end-to-end disparity regression effectively. We evaluate our network on Scene Flow, KITTI2012, and KITTI2015 datasets, and the experimental results show that the speed and accuracy of our method are excellent.

scholarly journals A Taillight Matching and Pairing Algorithm for Stereo-Vision-Based Nighttime Vehicle-to-Vehicle Positioning

2020 ◽  
Vol 10 (19) ◽  
pp. 6800
Author(s):  
Thai-Hoa Huynh ◽  
Myungsik Yoo
Keyword(s):  
Stereo Vision ◽  
Autonomous Vehicles ◽  
Stereo Matching ◽  
Vision System ◽  
Urban Traffic ◽  
Vehicle To Vehicle ◽  
Potential Benefits ◽  
Vehicle Positioning ◽  
Left Image ◽  
The Right

The stereo vision system has several potential benefits for delivering advanced autonomous vehicles compared to other existing technologies, such as vehicle-to-vehicle (V2V) positioning. This paper explores a stereo-vision-based nighttime V2V positioning process by detecting vehicle taillights. To address the crucial problems when applying this process to urban traffic, we propose a three-fold contribution as follows. The first contribution is a detection method that aims to label and determine the pixel coordinates of every taillight region from the images. Second, a stereo matching method derived from a gradient boosted tree is proposed to determine which taillight in the left image a taillight in the right image corresponds to. Third, we offer a neural-network-based method to pair every two taillights that belong to the same vehicle. The experiment on the four-lane traffic road was conducted, and the results were used to quantitatively evaluate the performance of each proposed method in real situations.

scholarly journals High-Accuracy Recognition and Localization of Moving Targets in an Indoor Environment Using Binocular Stereo Vision

2021 ◽  
Vol 10 (4) ◽  
pp. 234
Author(s):  
Jing Ding ◽  
Zhigang Yan ◽  
Xuchen We
Keyword(s):  
Stereo Vision ◽  
Stereo Matching ◽  
Three Dimensional ◽  
Target Localization ◽  
Parallel Structure ◽  
Moving Target ◽  
Target Area ◽  
Moving Targets ◽  
Binocular Stereo Vision ◽  
Binocular Stereo

To obtain effective indoor moving target localization, a reliable and stable moving target localization method based on binocular stereo vision is proposed in this paper. A moving target recognition extraction algorithm, which integrates displacement pyramid Horn–Schunck (HS) optical flow, Delaunay triangulation and Otsu threshold segmentation, is presented to separate a moving target from a complex background, called the Otsu Delaunay HS (O-DHS) method. Additionally, a stereo matching algorithm based on deep matching and stereo vision is presented to obtain dense stereo matching points pairs, called stereo deep matching (S-DM). The stereo matching point pairs of the moving target were extracted with the moving target area and stereo deep matching point pairs, then the three dimensional coordinates of the points in the moving target area were reconstructed according to the principle of binocular vision’s parallel structure. Finally, the moving target was located by the centroid method. The experimental results showed that this method can better resist image noise and repeated texture, can effectively detect and separate moving targets, and can match stereo image points in repeated textured areas more accurately and stability. This method can effectively improve the effectiveness, accuracy and robustness of three-dimensional moving target coordinates.

scholarly journals Artifact-Free Single Image Defogging

Atmosphere ◽  
2021 ◽  
Vol 12 (5) ◽  
pp. 577
Author(s):  
Gabriele Graffieti ◽  
Davide Maltoni
Keyword(s):  
Learning Strategy ◽  
Real Data ◽  
Training Procedure ◽  
Single Image ◽  
Paired Data ◽  
Manual Inspection ◽  
Synthetic Datasets ◽  
Visibility Enhancement ◽  
Difficult Cases ◽  
Good Contrast

In this paper, we present a novel defogging technique, named CurL-Defog, with the aim of minimizing the insertion of artifacts while maintaining good contrast restoration and visibility enhancement. Many learning-based defogging approaches rely on paired data, where fog is artificially added to clear images; this usually provides good results on mildly fogged images but is not effective for difficult cases. On the other hand, the models trained with real data can produce visually impressive results, but unwanted artifacts are often present. We propose a curriculum learning strategy and an enhanced CycleGAN model to reduce the number of produced artifacts, where both synthetic and real data are used in the training procedure. We also introduce a new metric, called HArD (Hazy Artifact Detector), to numerically quantify the number of artifacts in the defogged images, thus avoiding the tedious and subjective manual inspection of the results. HArD is then combined with other defogging indicators to produce a solid metric that is not deceived by the presence of artifacts. The proposed approach compares favorably with state-of-the-art techniques on both real and synthetic datasets.

Politieke statistiek in België : Oproep bij het einde van 170 jaar België

Res Publica ◽  
2000 ◽  
Vol 42 (2-3) ◽  
pp. 379-389
Author(s):  
Wilfried Dewachter
Keyword(s):  
20Th Century ◽  
19Th Century ◽  
Statistical Data ◽  
Depth Information ◽  
Global Approach ◽  
Institutional Approach ◽  
Static View ◽  
The Right ◽  
The 19Th Century

The great promises that "Statistik" yielded in the 19th century in Belgium, did  not materialise. At least as far as political statistics are concerned. In the second half of the 20th century the output was rather limited and thus very incomplete, not very professionally conceived and elaborated, disorderly provided, strongly related to an outrunned institutional approach and thus quite conservative in its orientation, veiled in inaccurate categories with the static view rather dominant. Therefore, starting from a global approach of the 3 P's (=polity, politics and policy), a rebuilding is necessary. This should provide for an inventory of existing statistical data and -above all -a masterplan to achieve a straightforward view on the 3 P's in Belgium: polity, politics and policy. A polyarchy has the right and the need to in depth information that is as complete as feasible. Statistics are very handy tools to provide this information to both policymakers and citizens.

Research and Realization of a New Algorithm for Stereo Matching Based on Binocular Vision

2013 ◽  
Vol 670 ◽  
pp. 202-207 ◽  
Author(s):  
Jun Ting Cheng ◽  
C. Zhao ◽  
W.L. Zhao ◽  
W.H. Wu
Keyword(s):  
Binocular Vision ◽  
Stereo Matching ◽  
Three Dimensional ◽  
Cnc Machining ◽  
Matching Algorithm ◽  
Evaluation Test ◽  
Three Dimensional Measurement ◽  
Binocular Stereo ◽  
Measuring Machine ◽  
3D Solid

In the development of a three-dimensional measurement system, binocular stereo matching is the most important and difficult. In the basis of introducing selective principles of matching algorithm, a new stereo matching algorithm for binocular vision is put forward that is named noncoded difference measuring distance. The algorithm effectively grapples with the problem of searching for the coincidence relation of raster and can efficiently and accurately obtain three-dimensional world coordinates of the entities. Experiment results show that this 3D measuring machine can effectively measure the 3D solid profile of free surface. During the evaluation test for accuracy, scan a standard plane. Fit all 3D points in one plane, and then the flatness value of this plane is obtained. The flatness value of the standard plane has been ultimately measured as: ± 0.0462mm, this measuring accuracy can completely satisfy the requirements of rapid prototyping or CNC machining, it as well as achieves the stated accuracy (± 0.05mm).

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