no code implementations • 16 Jan 2024 • Hessah Albanwan, Rongjun Qin, Yang Tang
Image fusion in Remote Sensing (RS) has been a consistent demand due to its ability to turn raw images of different resolutions, sources, and modalities into accurate, complete, and spatio-temporally coherent images.
1 code implementation • 16 Oct 2023 • Rongjun Qin, Guixiang Zhang, Yang Tang
Yet, there is no comprehensive analysis of their transferability, i. e., to which extent a model trained on a source domain can be readily applicable to a target domain.
no code implementations • 1 Oct 2023 • Ningli Xu, Rongjun Qin, Debao Huang, Fabio Remondino
Neural Radiance Fields (NeRF) offer the potential to benefit 3D reconstruction tasks, including aerial photogrammetry.
no code implementations • 17 Sep 2023 • Debao Huang, Rongjun Qin
Typically, photogrammetric point clouds are assessed through reference data such as LiDAR point clouds.
no code implementations • 23 Aug 2023 • Mostafa Elhashash, Rongjun Qin
However, the noises and outliers caused by stereo matching and the heterogenous geometric errors of the poses present a challenge for existing fusion algorithms, since they mostly assume Gaussian errors and predict fused results based on data from local spatial neighborhoods, which may inherit uncertainties from multiple depths resulting in lowered accuracy.
no code implementations • 23 Aug 2023 • Shuang Song, Rongjun Qin
Conflating/stitching 2. 5D raster digital surface models (DSM) into a large one has been a running practice in geoscience applications, however, conflating full-3D mesh models, such as those from oblique photogrammetry, is extremely challenging.
no code implementations • 8 May 2023 • Xiao Ling, Rongjun Qin
Texture mapping as a fundamental task in 3D modeling has been well established for well-acquired aerial assets under consistent illumination, yet it remains a challenge when it is scaled to large datasets with images under varying views and illuminations.
1 code implementation • 14 Feb 2023 • Ningli Xu, Rongjun Qin, Shuang Song
In this work, we provide a comprehensive review of the state-of-the-art (SOTA) point cloud registration methods, where we analyze and evaluate these methods using a diverse set of point cloud data from indoor to satellite sources.
no code implementations • 25 Oct 2022 • Hessah Albanwan, Rongjun Qin
All DL algorithms are robust to geometric configurations of stereo pairs and are less sensitive in comparison to the Census-SGM, while learning-based cost metrics can generalize on satellite images when trained on different datasets (airborne or ground-view).
no code implementations • 11 Oct 2022 • Zhengbang Zhu, Rongjun Qin, JunJie Huang, Xinyi Dai, Yang Yu, Yong Yu, Weinan Zhang
The increase in the measured performance, however, can have two possible attributions: a better understanding of user preferences, and a more proactive ability to utilize human bounded rationality to seduce user over-consumption.
no code implementations • 31 May 2022 • Mostafa Elhashash, Hessah Albanwan, Rongjun Qin
The evolution of mobile mapping systems (MMSs) has gained more attention in the past few decades.
no code implementations • 27 May 2022 • Hessah Albanwan, Rongjun Qin
Knowing that classical stereo matching methods such as Census-based semi-global-matching (SGM) are widely adopted to process different types of stereo data, we therefore, propose a finetuning method that takes advantage of disparity maps derived from SGM on target stereo data.
no code implementations • 8 Apr 2022 • Debao Huang, Mostafa Elhashash, Rongjun Qin
We performed our bundle adjustment using the proposed constraint and then produced 3D dense point clouds.
no code implementations • 8 Apr 2022 • Shuang Song, Rongjun Qin
Recovering surface albedos from photogrammetric images for realistic rendering and synthetic environments can greatly facilitate its downstream applications in VR/AR/MR and digital twins.
no code implementations • 8 Apr 2022 • Mostafa Elhashash, Rongjun Qin
However, existing approaches face challenges in applying dense matching for images with different viewpoints primarily due to large differences in object scale.
1 code implementation • 8 Apr 2022 • Shengxi Gui, Rongjun Qin, Yang Tang
We further improve the robustness of the method by 1) intergrading building segmentation based on HRNetV2 into our software; and 2) having implemented a decision strategy to identify complex buildings and directly generate mesh to avoid erroneous LoD2 reconstruction from a system point of view.
no code implementations • 9 Mar 2022 • Rongjun Qin, Feng Chen, Tonghan Wang, Lei Yuan, Xiaoran Wu, Zongzhang Zhang, Chongjie Zhang, Yang Yu
We demonstrate that the task representation can capture the relationship among tasks, and can generalize to unseen tasks.
no code implementations • 14 Feb 2022 • Xiao Ling, Rongjun Qin
In this paper, based on the assumption that the object boundaries (e. g., buildings) from the over-view data should coincide with footprints of fa\c{c}ade 3D points generated from street-view photogrammetric images, we aim to address this problem by proposing a fully automated geo-registration method for cross-view data, which utilizes semantically segmented object boundaries as view-invariant features under a global optimization framework through graph-matching: taking the over-view point clouds generated from stereo/multi-stereo satellite images and the street-view point clouds generated from monocular video images as the inputs, the proposed method models segments of buildings as nodes of graphs, both detected from the satellite-based and street-view based point clouds, thus to form the registration as a graph-matching problem to allow non-rigid matches; to enable a robust solution and fully utilize the topological relations between these segments, we propose to address the graph-matching problem on its conjugate graph solved through a belief-propagation algorithm.
no code implementations • 7 Feb 2022 • Rongjun Qin, Tao Liu
As an important application in remote sensing, landcover classification remains one of the most challenging tasks in very-high-resolution (VHR) image analysis.
1 code implementation • 8 Sep 2021 • Shengxi Gui, Rongjun Qin
In this paper, we propose a model-driven method that reconstructs LoD-2 building models following a "decomposition-optimization-fitting" paradigm.
1 code implementation • ICCV 2021 • Shuang Song, Zhaopeng Cui, Rongjun Qin
Then the visibility information of multiple views is aggregated to generate a 3D mesh model by solving an optimization problem considering visibility in which a novel adaptive visibility weighting in surface determination is also introduced to suppress line of sight with a large incident angle.
no code implementations • 18 Aug 2021 • Rongjun Qin, Armin Gruen, Cive Fraser
Recently developed automatic dense image matching algorithms are now being implemented for DSM/DTM production, with their pixel-level surface generation capability offering the prospect of partially alleviating the need for manual and semi-automatic stereoscopic measurements.
no code implementations • 5 Aug 2021 • Ningli Xu, Debao Huang, Shuang Song, Xiao Ling, Chris Strasbaugh, Alper Yilmaz, Halil Sezen, Rongjun Qin
In this paper, we present a case study that performs an unmanned aerial vehicle (UAV) based fine-scale 3D change detection and monitoring of progressive collapse performance of a building during a demolition event.
no code implementations • 6 Jul 2021 • Hessah Albanwan, Rongjun Qin
Remote sensing images and techniques are powerful tools to investigate earth surface.
no code implementations • 1 Jul 2021 • Xiao Ling, Xu Huang, Rongjun Qin
Bundle adjustment (BA) is a technique for refining sensor orientations of satellite images, while adjustment accuracy is correlated with feature matching results.
no code implementations • 1 Jul 2021 • Hessah Albanwan, Rongjun Qin, Xiaohu Lu, Mao Li, Desheng Liu, Jean-Michel Guldmann
The current practice in land cover/land use change analysis relies heavily on the individually classified maps of the multitemporal data set.
no code implementations • 1 Jul 2021 • Changlin Xiao, Rongjun Qin, Xiao Xie, Xu Huang
Individual tree detection and crown delineation (ITDD) are critical in forest inventory management and remote sensing based forest surveys are largely carried out through satellite images.
no code implementations • 27 Jun 2021 • Rongjun Qin, Shuang Song, Xiao Ling, Mostafa Elhashash
3D recovery from multi-stereo and stereo images, as an important application of the image-based perspective geometry, serves many applications in computer vision, remote sensing and Geomatics.
no code implementations • 27 Jun 2021 • Rongjun Qin, Xu Huang
Nowadays the image-based methods backboned by the recently developed advanced dense image matching algorithms and geo-referencing paradigms, are becoming the dominant approaches, due to its high flexibility, availability and low cost.
no code implementations • 27 Jun 2021 • Rongjun Qin
This article aims to provide an overview the state-of-the-art change detection methods in the field of Remote Sensing and Geomatics to support the task of updating geodatabases.
3 code implementations • 1 Feb 2021 • Rongjun Qin, Songyi Gao, Xingyuan Zhang, Zhen Xu, Shengkai Huang, Zewen Li, Weinan Zhang, Yang Yu
We evaluate existing offline RL algorithms on NeoRL and argue that the performance of a policy should also be compared with the deterministic version of the behavior policy, instead of the dataset reward.
no code implementations • ICCV 2021 • Zuoyue Li, Zhenqiang Li, Zhaopeng Cui, Rongjun Qin, Marc Pollefeys, Martin R. Oswald
For geometrical and temporal consistency, our approach explicitly creates a 3D point cloud representation of the scene and maintains dense 3D-2D correspondences across frames that reflect the geometric scene configuration inferred from the satellite view.
no code implementations • 22 May 2019 • Bihe Chen, Rongjun Qin, Xu Huang, Shuang Song, Xiaohu Lu
Stereo dense image matching can be categorized to low-level feature based matching and deep feature based matching according to their matching cost metrics.
no code implementations • 17 May 2019 • Rongjun Qin
Multiple depth maps derived from individual image pairs are fused with an adaptive 3D median filter that considers the image spectral similarities.
no code implementations • 17 May 2019 • Rongjun Qin
The intersection angle between two images are normally seen as the most important one in stereo data acquisition, as the state-of-the-art DIM algorithms work best on narrow baseline (smaller intersection angle) stereos (E. g. Semi-Global Matching regards 15-25 degrees as good intersection angle).