scholarly journals Group-Based Atrous Convolution Stereo Matching Network

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Qijie Zou ◽  
Jing Yu ◽  
Hui Fang ◽  
Jing Qin ◽  
Jie Zhang ◽  
...  
Keyword(s):  
Receptive Field ◽  
Stereo Matching ◽  
Multiple Scales ◽  
Contextual Information ◽  
Computation Time ◽  
Depth Estimation ◽  
Memory Storage ◽  
Stereo Pair ◽  
Matching Network ◽  
The Impact

Stereo matching is the key technology in stereo vision. Given a pair of rectified images, stereo matching determines correspondences between the pair images and estimate depth by obtaining disparity between corresponding pixels. The current work has shown that depth estimation from a stereo pair of images can be formulated as a supervised learning task with an end-to-end frame based on convolutional neural networks (CNNs). However, 3D CNN puts a great burden on memory storage and computation, which further leads to the significantly increased computation time. To alleviate this issue, atrous convolution was proposed to reduce the number of convolutional operations via a relatively sparse receptive field. However, this sparse receptive field makes it difficult to find reliable corresponding points in fuzzy areas, e.g., occluded areas and untextured areas, owing to the loss of rich contextual information. To address this problem, we propose the Group-based Atrous Convolution Spatial Pyramid Pooling (GASPP) to robustly segment objects at multiple scales with affordable computing resources. The main feature of the GASPP module is to set convolutional layers with continuous dilation rate in each group, so that it can reduce the impact of holes introduced by atrous convolution on network performance. Moreover, we introduce a tailored cascade cost volume in a pyramid form to reduce memory, so as to meet real-time performance. The group-based atrous convolution stereo matching network is evaluated on the street scene benchmark KITTI 2015 and Scene Flow and achieves state-of-the-art performance.

scholarly journals Event-based stereo matching using semiglobal matching

2018 ◽  
Vol 15 (1) ◽  
pp. 172988141775275 ◽  
Author(s):  
Zhen Xie ◽  
Jianhua Zhang ◽  
Pengfei Wang
Keyword(s):  
Stereo Matching ◽  
Dynamic Range ◽  
Three Dimensional ◽  
Depth Estimation ◽  
Estimation Algorithm ◽  
Frame Rate ◽  
Estimation Accuracy ◽  
High Temporal Resolution ◽  
Stereo Pair ◽  
Event Based

In this article, we focus on the problem of depth estimation from a stereo pair of event-based sensors. These sensors asynchronously capture pixel-level brightness changes information (events) instead of standard intensity images at a specified frame rate. So, these sensors provide sparse data at low latency and high temporal resolution over a wide intrascene dynamic range. However, new asynchronous, event-based processing algorithms are required to process the event streams. We propose a fully event-based stereo three-dimensional depth estimation algorithm inspired by semiglobal matching. Our algorithm considers the smoothness constraints between the nearby events to remove the ambiguous and wrong matches when only using the properties of a single event or local features. Experimental validation and comparison with several state-of-the-art, event-based stereo matching methods are provided on five different scenes of event-based stereo data sets. The results show that our method can operate well in an event-driven way and has higher estimation accuracy.

scholarly journals A Semi-Supervised Monocular Stereo Matching Method

Symmetry ◽  
2019 ◽  
Vol 11 (5) ◽  
pp. 690
Author(s):  
Zhimin Zhang ◽  
Jianzhong Qiao ◽  
Shukuan Lin
Keyword(s):  
Stereo Matching ◽  
Ground Truth ◽  
Depth Estimation ◽  
Estimation Methods ◽  
Estimation Accuracy ◽  
Stereo Pair ◽  
Single Image ◽  
Matching Method ◽  
Matching Model ◽  
Monocular Depth

Supervised monocular depth estimation methods based on learning have shown promising results compared with the traditional methods. However, these methods require a large number of high-quality corresponding ground truth depth data as supervision labels. Due to the limitation of acquisition equipment, it is expensive and impractical to record ground truth depth for different scenes. Compared to supervised methods, the self-supervised monocular depth estimation method without using ground truth depth is a promising research direction, but self-supervised depth estimation from a single image is geometrically ambiguous and suboptimal. In this paper, we propose a novel semi-supervised monocular stereo matching method based on existing approaches to improve the accuracy of depth estimation. This idea is inspired by the experimental results of the paper that the depth estimation accuracy of a stereo pair as input is better than that of a monocular view as input in the same self-supervised network model. Therefore, we decompose the monocular depth estimation problem into two sub-problems, a right view synthesized process followed by a semi-supervised stereo matching process. In order to improve the accuracy of the synthetic right view, we innovate beyond the existing view synthesis method Deep3D by adding a left-right consistency constraint and a smoothness constraint. To reduce the error caused by the reconstructed right view, we propose a semi-supervised stereo matching model that makes use of disparity maps generated by a self-supervised stereo matching model as the supervision cues and joint self-supervised cues to optimize the stereo matching network. In the test, the two networks are able to predict the depth map directly from a single image by pipeline connecting. Both procedures not only obey geometric principles, but also improve estimation accuracy. Test results on the KITTI dataset show that this method is superior to the current mainstream monocular self-supervised depth estimation methods under the same condition.

Methods for Restricting Maximum Exposure Rate in Computerized Adaptative Testing

Methodology ◽  
2007 ◽  
Vol 3 (1) ◽  
pp. 14-23 ◽  
Author(s):  
Juan Ramon Barrada ◽  
Julio Olea ◽  
Vicente Ponsoda
Keyword(s):  
Measurement Accuracy ◽  
Computerized Adaptive Testing ◽  
Computation Time ◽  
Adaptive Testing ◽  
Exposure Rate ◽  
Control Parameters ◽  
The Impact ◽  
Two Alternatives ◽  
Selection Of ◽  
Maximum Exposure

Abstract. The Sympson-Hetter (1985) method provides a means of controlling maximum exposure rate of items in Computerized Adaptive Testing. Through a series of simulations, control parameters are set that mark the probability of administration of an item on being selected. This method presents two main problems: it requires a long computation time for calculating the parameters and the maximum exposure rate is slightly above the fixed limit. Van der Linden (2003) presented two alternatives which appear to solve both of the problems. The impact of these methods in the measurement accuracy has not been tested yet. We show how these methods over-restrict the exposure of some highly discriminating items and, thus, the accuracy is decreased. It also shown that, when the desired maximum exposure rate is near the minimum possible value, these methods offer an empirical maximum exposure rate clearly above the goal. A new method, based on the initial estimation of the probability of administration and the probability of selection of the items with the restricted method ( Revuelta & Ponsoda, 1998 ), is presented in this paper. It can be used with the Sympson-Hetter method and with the two van der Linden's methods. This option, when used with Sympson-Hetter, speeds the convergence of the control parameters without decreasing the accuracy.

scholarly journals DSM Generation from Single and Cross-Sensor Multi-View Satellite Images Using the New Agisoft Metashape: The Case Studies of Trento and Matera (Italy)

2021 ◽  
Vol 13 (4) ◽  
pp. 593
Author(s):  
Lorenzo Lastilla ◽  
Valeria Belloni ◽  
Roberta Ravanelli ◽  
Mattia Crespi
Keyword(s):  
Case Studies ◽  
Accuracy Assessment ◽  
Stereo Pair ◽  
Commercial Software ◽  
Processing Module ◽  
Land Covers ◽  
Image Metadata ◽  
The Impact ◽  
The City ◽  
Reliable Software

DSM generation from satellite imagery is a long-lasting issue and it has been addressed in several ways over the years; however, expert and users are continuously searching for simpler but accurate and reliable software solutions. One of the latest ones is provided by the commercial software Agisoft Metashape (since version 1.6), previously known as Photoscan, which joins other already available open-source and commercial software tools. The present work aims to quantify the potential of the new Agisoft Metashape satellite processing module, considering that to the best knowledge of the authors, only two papers have been published, but none considering cross-sensor imagery. Here we investigated two different case studies to evaluate the accuracy of the generated DSMs. The first dataset consists of a triplet of Pléiades images acquired over the area of Trento and the Adige valley (Northern Italy), which is characterized by a great variety in terms of geomorphology, land uses and land covers. The second consists of a triplet composed of a WorldView-3 stereo pair and a GeoEye-1 image, acquired over the city of Matera (Southern Italy), one of the oldest settlements in the world, with the worldwide famous area of Sassi and a very rugged morphology in the surroundings. First, we carried out the accuracy assessment using the RPCs supplied by the satellite companies as part of the image metadata. Then, we refined the RPCs with an original independent terrain technique able to supply a new set of RPCs, using a set of GCPs adequately distributed across the regions of interest. The DSMs were generated both in a stereo and multi-view (triplet) configuration. We assessed the accuracy and completeness of these DSMs through a comparison with proper references, i.e., DSMs obtained through LiDAR technology. The impact of the RPC refinement on the DSM accuracy is high, ranging from 20 to 40% in terms of LE90. After the RPC refinement, we achieved an average overall LE90 <5.0 m (Trento) and <4.0 m (Matera) for the stereo configuration, and <5.5 m (Trento) and <4.5 m (Matera) for the multi-view (triplet) configuration, with an increase of completeness in the range 5–15% with respect to stereo pairs. Finally, we analyzed the impact of land cover on the accuracy of the generated DSMs; results for three classes (urban, agricultural, forest and semi-natural areas) are also supplied.

scholarly journals Impact of COVID-19 Pandemic on Retail Structure in Barcelona: From Tourism-Phobia to the Desertification of City Center

2021 ◽  
Vol 13 (15) ◽  
pp. 8215
Author(s):  
Lluís Frago Clols
Keyword(s):  
Multiple Scales ◽  
Real Estate Market ◽  
Structured Interviews ◽  
City Center ◽  
Urban Theory ◽  
The Real Estate ◽  
Tourist Flows ◽  
Before And After ◽  
The Impact ◽  
The City

COVID-19 has meant major transformations for commercial fabric. These transformations have been motivated by the collapse of consumer mobility at multiple scales. We analyzed the impact of the collapse of global tourist flows on the commercial fabric of Barcelona city center, a city that has been a global reference in over-tourism and tourism-phobia. Fieldwork in the main commercial areas before and after the pandemic and complementary semi-structured interviews with the main agents involved highlight the relationship between global tourist flows and commercial fabric. The paper shows how the end of global tourism has meant an important commercial desertification. The end of the integration of the city center into global consumer flows has implications for urban theory. It means a downscaling of the city center and the questioning of traditional center-periphery dynamics. It has been shown that the tourist specialization of commerce has important effects on the real estate market and makes it particularly vulnerable. However, the touristic specialization of commercial activities as a strategy of resilience has also been presented. This adaptation faces the generalized commercial desertification that drives the growing concentration of consumption around the online channel.

scholarly journals The Impacts of Groundwater Chemistry on Wetland Vegetation Distribution in the Northern Qinghai–Tibet Plateau

2019 ◽  
Vol 11 (18) ◽  
pp. 5022 ◽  
Author(s):  
Junju Zhou ◽  
Juan Xiang ◽  
Lanying Wang ◽  
Guoshuang Zhong ◽  
Guofeng Zhu ◽  
...  
Keyword(s):  
Multiple Scales ◽  
Groundwater Chemistry ◽  
Ion Concentration ◽  
Tibet Plateau ◽  
Distribution Data ◽  
Vegetation Distribution ◽  
Chemical Parameters ◽  
Weakly Alkaline ◽  
Artemisia Frigida ◽  
The Impact

Groundwater chemistry has an important impact on the vegetation distribution in inland areas. An in-depth understanding of the impact of groundwater chemistry on vegetation can help in developing an effective management strategy to protect the inland ecosystem. The aim of this study was to identify the influence of groundwater chemicals on species diversity and the distribution characteristics of wetland plants at multiple scales based on the groundwater chemical data from 15 sampling points and the distribution data of 13 plants in the Sugan Lake Wetland in 2016. The results show that the groundwater of the Sugan Lake Wetland is weakly alkaline, with high salinity and hardness; the water chemical type is Na-SO4-Cl; the concentration of the major water chemical parameters is significantly different and is the highest in the northwest, followed by the southwest, and is the lowest in the east; with an increase in the groundwater depth, the concentration of major water chemical parameters first showed an increasing trend followed by a decreasing trend; Artemisia frigida Willd, Poa annua L. and Triglochin maritimum L. were adapted to the environment with a higher ion concentration of the groundwater, and their salt resistance was the strongest; Blysmus sinocompressus and Polygonum are more adapted to the environment with lower salinity and hardness of groundwater; Thermopsis lanceolata has stronger adaptability to the ion concentration, salinity, and hardness of groundwater; other plants are adapted to environments where the ion concentration, salinity, and hardness of the groundwater are moderate.

The Impact of Stationarity, Regularity, and Context on the Predictability of Individual Human Mobility

2021 ◽  
Vol 7 (4) ◽  
pp. 1-24
Author(s):  
Douglas Do Couto Teixeira ◽  
Aline Carneiro Viana ◽  
Jussara M. Almeida ◽  
Mrio S. Alvim
Keyword(s):  
State Of The Art ◽  
Human Mobility ◽  
Contextual Information ◽  
Prediction Method ◽  
Mobility Prediction ◽  
Mobility Patterns ◽  
Distinct Cell ◽  
Inherent Nature ◽  
The One ◽  
The Impact

Predicting mobility-related behavior is an important yet challenging task. On the one hand, factors such as one’s routine or preferences for a few favorite locations may help in predicting their mobility. On the other hand, several contextual factors, such as variations in individual preferences, weather, traffic, or even a person’s social contacts, can affect mobility patterns and make its modeling significantly more challenging. A fundamental approach to study mobility-related behavior is to assess how predictable such behavior is, deriving theoretical limits on the accuracy that a prediction model can achieve given a specific dataset. This approach focuses on the inherent nature and fundamental patterns of human behavior captured in that dataset, filtering out factors that depend on the specificities of the prediction method adopted. However, the current state-of-the-art method to estimate predictability in human mobility suffers from two major limitations: low interpretability and hardness to incorporate external factors that are known to help mobility prediction (i.e., contextual information). In this article, we revisit this state-of-the-art method, aiming at tackling these limitations. Specifically, we conduct a thorough analysis of how this widely used method works by looking into two different metrics that are easier to understand and, at the same time, capture reasonably well the effects of the original technique. We evaluate these metrics in the context of two different mobility prediction tasks, notably, next cell and next distinct cell prediction, which have different degrees of difficulty. Additionally, we propose alternative strategies to incorporate different types of contextual information into the existing technique. Our evaluation of these strategies offer quantitative measures of the impact of adding context to the predictability estimate, revealing the challenges associated with doing so in practical scenarios.

Impact of Contextual Information on Automation Brittleness

2002 ◽  
Vol 46 (3) ◽  
pp. 382-386 ◽  
Author(s):  
Jennifer J. Ockerman ◽  
Amy R. Pritchett
Keyword(s):  
Contextual Information ◽  
Decision Aids ◽  
System Function ◽  
Commercial Aircraft ◽  
Complex Automation ◽  
The Impact

Brittleness, the inability to provide accurate assistance in all situations, is frequently an issue with complex automation and automatic decision aids. This paper examines a method of mitigating the impact of brittleness on overall system function. Using the task of planning an emergency descent for a commercial aircraft, this study found that the presence of contextual information in the presentation of an automatically generated emergency descent procedure might aid in mitigating the effects of automation brittleness. By providing pilots with rationale as to the design of the descent procedure, the pilots were better able to correctly determine why a provided procedure was or was not feasible.

Robust Scale-Aware Stereo Matching Network

2021 ◽  
pp. 1-1
Author(s):  
James Okae ◽  
Bohan Li ◽  
Juan Du ◽  
Yueming Hu
Keyword(s):  
Stereo Matching ◽  
Matching Network

An Empirical Study on the Impact of Design Brief Information on the Creativity of Design Outcomes With Consideration of Gender and Gender Diversity

2019 ◽  
Vol 141 (7) ◽  
Author(s):  
Georgios Koronis ◽  
Pei Zhi Chia ◽  
Jacob Kang Kai Siang ◽  
Arlindo Silva ◽  
Christine Yogiaman ◽  
...  
Keyword(s):  
Empirical Study ◽  
Undergraduate Student ◽  
Contextual Information ◽  
Gender Diversity ◽  
First Year ◽  
Main Effect ◽  
And Gender ◽  
The Impact ◽  
Collaborative Sketching

This study aims to understand how information in design briefs affects the creativity of design outcomes. We tested this during a Collaborative Sketching (C-Sketch) ideation exercise with first-year undergraduate student designers. We focus on four types of stimuli—quantitative requirements, a visual example (video), a physical example, and contextual information—and we measure creativity according to three metrics—novelty, appropriateness, and usability with either the participants’ gender or the gender diversity of the participants’ groups. The findings suggest that the main effect of providing a video example results in high appropriateness and usability scores but low novelty scores and that physical-contextual briefs have high novelty and usability scores. In addition, we did not find any correlation between gender or gender diversity and creativity scores.

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