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Your search keyword '"Weng, Duojie"' showing total 116 results
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116 results on '"Weng, Duojie"'

1. 3D Reconstruction of Spherical Images based on Incremental Structure from Motion

Author

Jiang, San, You, Kan, Li, Yaxin, Weng, Duojie, and Chen, Wu

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

3D reconstruction plays an increasingly important role in modern photogrammetric systems. Conventional satellite or aerial-based remote sensing (RS) platforms can provide the necessary data sources for the 3D reconstruction of large-scale landforms and cities. Even with low-altitude UAVs (Unmanned Aerial Vehicles), 3D reconstruction in complicated situations, such as urban canyons and indoor scenes, is challenging due to the frequent tracking failures between camera frames and high data collection costs. Recently, spherical images have been extensively exploited due to the capability of recording surrounding environments from one camera exposure. Classical 3D reconstruction pipelines, however, cannot be used for spherical images. Besides, there exist few software packages for 3D reconstruction of spherical images. Based on the imaging geometry of spherical cameras, this study investigates the algorithms for the relative orientation using spherical correspondences, absolute orientation using 3D correspondences between scene and spherical points, and the cost functions for BA (bundle adjustment) optimization. In addition, an incremental SfM (Structure from Motion) workflow has been proposed for spherical images using the above-mentioned algorithms. The proposed solution is finally verified by using three spherical datasets captured by both consumer-grade and professional spherical cameras. The results demonstrate that the proposed SfM workflow can achieve the successful 3D reconstruction of complex scenes and provide useful clues for the implementation in open-source software packages. The source code of the designed SfM workflow would be made publicly available.

Published
2023

2. 3D reconstruction from spherical images: A review of techniques, applications, and prospects

Author

Jiang, San, Li, Yaxin, Weng, Duojie, You, Kan, and Chen, Wu

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

3D reconstruction plays an increasingly important role in modern photogrammetric systems. Conventional satellite or aerial-based remote sensing (RS) platforms can provide the necessary data sources for the 3D reconstruction of large-scale landforms and cities. Even with low-altitude UAVs (Unmanned Aerial Vehicles), 3D reconstruction in complicated situations, such as urban canyons and indoor scenes, is challenging due to frequent tracking failures between camera frames and high data collection costs. Recently, spherical images have been extensively used due to the capability of recording surrounding environments from one camera exposure. In contrast to perspective images with limited FOV (Field of View), spherical images can cover the whole scene with full horizontal and vertical FOV and facilitate camera tracking and data acquisition in these complex scenes. With the rapid evolution and extensive use of professional and consumer-grade spherical cameras, spherical images show great potential for the 3D modeling of urban and indoor scenes. Classical 3D reconstruction pipelines, however, cannot be directly used for spherical images. Besides, there exist few software packages that are designed for the 3D reconstruction of spherical images. As a result, this research provides a thorough survey of the state-of-the-art for 3D reconstruction of spherical images in terms of data acquisition, feature detection and matching, image orientation, and dense matching as well as presenting promising applications and discussing potential prospects. We anticipate that this study offers insightful clues to direct future research.

Published
2023

17. Equalization of Frequency Domain Adaptive Filter (FDAF) Using Signal Prediction Aided Reference Spectrum Model (SPRSM)

Author

Ding, Mengyu, Mi, Xiaolong, Chen, Wu, Weng, Duojie, and Ding, Weihao

Abstract

Filtering jamming signals from intermediate frequency (IF) data is a practical anti-jamming solution for low-cost global navigation satellite system (GNSS) receivers, as it does not change antennas or baseband structures. Frequency domain adaptive filter (FDAF) is a commonly used IF anti-jamming filter, which removes jamming components in the frequency domain. However, this filter also filters out normal satellite signals within the jamming bands, resulting in significant signal distortions. These distortions can negatively impact signal quality and positioning accuracy. To address this issue, this study focuses on improving the performance of FDAF by incorporating a signal-prediction-aided reference spectrum model (SPRSM) equalizer. Initially, the signal loss caused by FDAF is analyzed. Then, the SPRSM equalizer is developed, which differs from classical equalizers that rely on an empirical normal spectrum. Instead, the SPRSM equalizer utilizes GNSS predictions to compensate for distortions. The effectiveness of the SPRSM equalizer is then theoretically compared to that of the classical equalizer, specifically in terms of carrier-to-noise-density ratio (C/N0) improvement. Real-data experiments are conducted to further evaluate the superiority of the SPRSM equalizer over FDAF and FDAF with the classical equalizer. Specifically, the experimental results show that the SPRSM equalizer can handle narrowband sweep continuous wave interference (SCWI) intensities up to 10 and 6 dB higher than standalone FDAF and the classical equalizer, respectively, while still maintaining a C/N0 over 27 dB $\cdot $ Hz of tracking threshold. Under bandlimited noise (BN) scenarios, the intensities that SPRSM equalizer can handle are up to 6 and 4 dB higher than that of standalone FDAF and the classical equalizer, respectively. Moreover, when subjected to the same jamming attacks, the SPRSM equalizer demonstrates a 11%–60% improvement in horizontal positioning accuracy compared to the classical equalizer.

Published
2024
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20. Deformation monitoring using daily repeated GNSS-R data

Author

Yang, Yang, He, Zhenyu, Weng, Duojie, and Chen, Wu

Abstract

GNSS reflectometry has been proved to possess the capabilities for deformation monitoring by observing the carrier phase difference between the direct and reflected signals. However, to obtain the carrier phase measurement, the requirements to signal quality and monitoring geometry is relatively strict, and the application of this method is limited because of the requirement of continuous observation and the involvement of software defined radio (SDR) receiver. We present an innovative deformation monitoring method of observing signal-to-noise ratio (SNR) oscillation pattern of the interference of direct and reflected signals, by using daily repeated GNSS-R data. The direct and reflected signals were merged by radio frequency combiner, then fed into an off-the-shelf commercial GNSS receiver. Then the SNR of the interference signal can be directly outputted and recorded, and the oscillation pattern between observation days have been aligned by geometry model, and the phase shift of the oscillation pattern can be analyzed for deformation monitoring. The field experiment results show sub-centimeter level accuracy with more than 300 meters monitoring range. This new method possesses the advantages of robust, low data size and computational burden, and long monitoring range. Especially, without need of continuous observation and applicable for commercial GNSS receiver make this method more practical for long-term quasi-static deformation monitoring., The 28th IUGG General Assembly (IUGG2023) (Berlin 2023)

Published
2023

25. An Atmospheric Phase Correction Method Based on Normal Vector Clustering Partition in Complicated Conditions for GB-SAR.

Author

Ou, Pengfei, Lai, Tao, Huang, Shisheng, Chen, Wu, and Weng, Duojie

Subjects
SPACE-based radar, SYNTHETIC aperture radar, WEATHER
Abstract

Atmospheric phase is the main factor affecting the accuracy of ground-based synthetic aperture radar. The atmospheric phase screen (APS) may be very complicated, due to the drastic changes in atmospheric conditions, and the conventional correction methods based on regression models cannot fit and correct it effectively. Partition correction is a feasible path to improve atmospheric phase correction (APC) accuracy for complicated APS, but the overfitting problem cannot be ignored. In this article, we propose a clustering partition method, based on the normal vector of APS, which can partition the complicated APS more reasonably, and then perform APC based on the partition results. APC, and simulation experiments on measurement data, suggests that the proposed method achieves higher accuracy than the conventional model-based methods for complicated APS and avoids severe overfitting, realizing the balance between accuracy and credibility. This article verifies the feasibility and effectiveness of using APS distribution information to guide the partition and conduct APC. [ABSTRACT FROM AUTHOR]

Published
2023
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