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[IEEE 2018 Conference on Design and Architectures for Signal and Image Processing (DASIP) - Porto, Portugal (2018.10.10-2018.10.12)] 2018 Conference on Design and Architectures for Signal and Image Processing (DASIP) - Hardware-Software Implementation of a SFM Module for Navigation an Unmanned Aerial Vehicles-A Demo
摘要： In this paper the design of an embedded vision system for structure from motion (SFM) computation is presented. The solution allows for scene depth reconstruction based on two consecutive video frames registered by a moving camera. The module is developed for a Xilinx Zynq SoC (System on Chip) device and is divided into a hardware and software part. The programmable logic (PL) is used mainly for detect and match features. Fundamental matrix estimation and triangulation are executed in the processing system (PS – ARM based). The module is dedicated to navigation of unmanned aerial vehicles (UAV) – autonomous flight and landing. The system is adapted to process a 1280x720 pixel video stream @60 frames per second in real-time.
关键词： FPGA,Zynq SoC,structure from motion,real-time video processing,hardware-software systems
更新于2025-09-23 15:22:29
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Evaluation of Ground Surface Models Derived from Unmanned Aerial Systems with Digital Aerial Photogrammetry in a Disturbed Conifer Forest
摘要： Detailed vertical forest structure information can be remotely sensed by combining technologies of unmanned aerial systems (UAS) and digital aerial photogrammetry (DAP). A key limitation in the application of DAP methods, however, is the inability to produce accurate digital elevation models (DEM) in areas of dense vegetation. This study investigates the terrain modeling potential of UAS-DAP methods within a temperate conifer forest in British Columbia, Canada. UAS-acquired images were photogrammetrically processed to produce high-resolution DAP point clouds. To evaluate the terrain modeling ability of DAP, first, a sensitivity analysis was conducted to estimate optimal parameters of three ground-point classification algorithms designed for airborne laser scanning (ALS). Algorithms tested include progressive triangulated irregular network (TIN) densification (PTD), hierarchical robust interpolation (HRI) and simple progressive morphological filtering (SMRF). Points were classified as ground from the ALS and served as ground-truth data to which UAS-DAP derived DEMs were compared. The proportion of area with root mean square error (RMSE) <1.5 m were 56.5%, 51.6% and 52.3% for the PTD, HRI and SMRF methods respectively. To assess the influence of terrain slope and canopy cover, error values of DAP-DEMs produced using optimal parameters were compared to stratified classes of canopy cover and slope generated from ALS point clouds. Results indicate that canopy cover was approximately three times more influential on RMSE than terrain slope.
关键词： Structure from Motion (SfM),point cloud classification,unmanned aerial systems (UAS),digital elevation model (DEM)
更新于2025-09-23 15:22:29
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[Lecture Notes in Computer Science] Pattern Recognition and Computer Vision Volume 11256 (First Chinese Conference, PRCV 2018, Guangzhou, China, November 23-26, 2018, Proceedings, Part I) || Large-Scale Structure from Motion with Semantic Constraints of Aerial Images
摘要： Structure from Motion (SfM) and semantic segmentation are two branches of computer vision. However, few previous methods integrate the two branches together. SfM is limited by the precision of traditional feature detecting method, especially in complicated scenes. As the research ?eld of semantic segmentation thrives, we could gain semantic information of high con?dence in each speci?c task with little e?ort. By utilizing semantic segmentation information, our paper presents a new way to boost the accuracy of feature point matching. Besides, with the semantic constraints taken from the result of semantic segmentation, a new bundle adjustment method with equality constraint is proposed. By exploring the sparsity of equality constraint, it indicates that constrained bundle adjustment can be solved by Sequential Quadratic Programming (SQP) e?ciently. The proposed approach achieves state of the art accuracy, and, by grouping the descriptors together by their semantic labels, the speed of putative matches is slightly boosted. Moreover, our approach demonstrates a potential of automatic labeling of semantic segmentation. In a nutshell, our work strongly veri?es that SfM and semantic segmentation bene?t from each other.
关键词： Sequential Quadratic Programming,Equality bundle adjustment,Semantic segmentation,Structure from Motion
更新于2025-09-23 15:21:01
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[IEEE 2018 IEEE 23rd International Conference on Emerging Technologies and Factory Automation (ETFA) - Torino, Italy (2018.9.4-2018.9.7)] 2018 IEEE 23rd International Conference on Emerging Technologies and Factory Automation (ETFA) - A single camera inspection system to detect and localize obstacles on railways based on manifold Kalman filtering
摘要： Railway line surveillance is important for providing safe and smooth travel of trains under effects of environmental or human-generated damages to the railway. This work presents a Structure from Motion pipeline specifically designed with the aim of supporting the monitoring operations of the railway infrastructure using a monocular camera mounted on the train’s tractor. Within this work we developed a dynamical reconstruction instrument based on the mathematics of the projective geometry for handling the problem of localization, by triangulation techniques of points, lines, whole objects and of other known elements. Exploiting the a-priori knowledge of the scene structure (known track gauge) and the camera intrinsic parameters it is possible to reconstruct in metric dimension the trajectory of the train and the position of the detected object. The approach proposed here combines Computer Vision techniques to detect the significant elements and to classify a set of features with Bayesian filtering. Algorithms for this specific purpose have been developed in order to identify the rail track geometry, and a line-based approach has been adopted to assess the camera poses. Starting from these first estimates, a manifold Unscented Kalman Filter operates on the set of robustly matched features, fusing heterogeneous cues about the camera orientation and using RANSAC to find the best solution. Consequently, the detected objects can be triangulated and localized. An analysis using real captures is reported to prove the quality of the results obtained.
关键词： RANSAC,Railway line surveillance,projective geometry,Bayesian filtering,monocular camera,Unscented Kalman Filter,Computer Vision,Structure from Motion
更新于2025-09-23 15:21:01
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Elliptical fibre dielectric waveguides: a transverse transmission line analysis
摘要： Non-rigid structure-from-motion (NRSfM) is the process of recovering time-varying 3D structures and poses of a deformable object from an uncalibrated monocular video sequence. Currently, most NRSfM algorithms utilize a non-degenerate assumption for non-rigid object deformations whereby the 3D structures of a non-rigid object can be assumed to be a linear combination of basis shapes with full rank three. Unfortunately, this assumption will produce extra degrees-of-freedom when the non-rigid object has some degenerate deformations with shape bases of rank less than three. These extra degrees-of-freedom will yield spurious shape deformations due to non-negligible noise in real applications, which will cause substantial reconstruction errors. To solve this problem, we propose a low-rank shape deformation model to represent 3D structures of degenerate deformations. When modeling degenerate deformations, the proposed model exploits the rank-deficient nature of degenerate deformations in addition to the low-rank property of non-rigid objects’ trajectories, thus providing a more accurate and compact representation compared with existing models. Based on this model, we formulate the NRSfM problem as two coherent optimization problems. These problems are solved with iterative non-linear optimization algorithms. Experiments on synthetic and motion capture data are conducted. The results exhibit the significant advantages of our approach over state-of-the-art NRSfM algorithms for the 3D recovery of non-rigid objects with degenerate deformations.
关键词： 3D reconstruction.,Degenerate deformations,non-rigid structure from motion,low-rank shape deformation model
更新于2025-09-23 15:19:57
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Automatic Process Parameters Tuning and Surface Roughness Estimation for Laser Cleaning
摘要： Non-rigid structure-from-motion (NRSfM) is the process of recovering time-varying 3D structures and poses of a deformable object from an uncalibrated monocular video sequence. Currently, most NRSfM algorithms utilize a non-degenerate assumption for non-rigid object deformations whereby the 3D structures of a non-rigid object can be assumed to be a linear combination of basis shapes with full rank three. Unfortunately, this assumption will produce extra degrees-of-freedom when the non-rigid object has some degenerate deformations with shape bases of rank less than three. These extra degrees-of-freedom will yield spurious shape deformations due to non-negligible noise in real applications, which will cause substantial reconstruction errors. To solve this problem, we propose a low-rank shape deformation model to represent 3D structures of degenerate deformations. When modeling degenerate deformations, the proposed model exploits the rank-deficient nature of degenerate deformations in addition to the low-rank property of non-rigid objects’ trajectories, thus providing a more accurate and compact representation compared with existing models. Based on this model, we formulate the NRSfM problem as two coherent optimization problems. These problems are solved with iterative non-linear optimization algorithms. Experiments on synthetic and motion capture data are conducted. The results exhibit the significant advantages of our approach over state-of-the-art NRSfM algorithms for the 3D recovery of non-rigid objects with degenerate deformations.
关键词： Degenerate deformations,non-rigid structure from motion,3D reconstruction,low-rank shape deformation model
更新于2025-09-23 15:19:57
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Examination of the Potential of Terrestrial Laser Scanning and Structure-from-Motion Photogrammetry for Rapid Nondestructive Field Measurement of Grass Biomass
摘要： Above ground biomass (AGB) is a parameter commonly used for assessment of grassland systems. Destructive AGB measurements, although accurate, are time consuming and are not easily undertaken on a repeat basis or over large areas. Structure-from-Motion (SfM) photogrammetry and Terrestrial Laser Scanning (TLS) are two technologies that have the potential to yield precise 3D structural measurements of vegetation quite rapidly. Recent advances have led to the successful application of TLS and SfM in woody biomass estimation, but application in natural grassland systems remains largely untested. The potential of these techniques for AGB estimation is examined considering 11 grass plots with a range of biomass in South Dakota, USA. Volume metrics extracted from the TLS and SfM 3D point clouds, and also conventional disc pasture meter settling heights, were compared to destructively harvested AGB total (grass and litter) and AGB grass plot measurements. Although the disc pasture meter was the most rapid method, it was less effective in AGB estimation (AGBgrass r2 = 0.42, AGBtotal r2 = 0.32) than the TLS (AGBgrass r2 = 0.46, AGBtotal r2 = 0.57) or SfM (AGBgrass r2 = 0.54, AGBtotal r2 = 0.72) which both demonstrated their utility for rapid AGB estimation of grass systems.
关键词： Structure-from-Motion (SfM) photogrammetry,disc pasture meter,grass,aboveground biomass (AGB),compact biomass LiDAR (CBL),terrestrial laser scanning (TLS),volume
更新于2025-09-16 10:30:52
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[IEEE 2019 41st Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) - Berlin, Germany (2019.7.23-2019.7.27)] 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) - Evaluation of the influence of cyclic loading on a laser sintered transtibial prosthetic socket using Digital Image Correlation (DIC)
摘要： Non-rigid structure-from-motion (NRSfM) is the process of recovering time-varying 3D structures and poses of a deformable object from an uncalibrated monocular video sequence. Currently, most NRSfM algorithms utilize a non-degenerate assumption for non-rigid object deformations whereby the 3D structures of a non-rigid object can be assumed to be a linear combination of basis shapes with full rank three. Unfortunately, this assumption will produce extra degrees-of-freedom when the non-rigid object has some degenerate deformations with shape bases of rank less than three. These extra degrees-of-freedom will yield spurious shape deformations due to non-negligible noise in real applications, which will cause substantial reconstruction errors. To solve this problem, we propose a low-rank shape deformation model to represent 3D structures of degenerate deformations. When modeling degenerate deformations, the proposed model exploits the rank-deficient nature of degenerate deformations in addition to the low-rank property of non-rigid objects’ trajectories, thus providing a more accurate and compact representation compared with existing models. Based on this model, we formulate the NRSfM problem as two coherent optimization problems. These problems are solved with iterative non-linear optimization algorithms. Experiments on synthetic and motion capture data are conducted. The results exhibit the significant advantages of our approach over state-of-the-art NRSfM algorithms for the 3D recovery of non-rigid objects with degenerate deformations.
关键词： Degenerate deformations,non-rigid structure from motion,3D reconstruction,low-rank shape deformation model
更新于2025-09-16 10:30:52
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A Lightweight Leddar Optical Fusion Scanning System (FSS) for Canopy Foliage Monitoring
摘要： A growing need for sampling environmental spaces in high detail is driving the rapid development of non-destructive three-dimensional (3D) sensing technologies. LiDAR sensors, capable of precise 3D measurement at various scales from indoor to landscape, still lack affordable and portable products for broad-scale and multi-temporal monitoring. This study aims to configure a compact and low-cost 3D fusion scanning system (FSS) with a multi-segment Leddar (light emitting diode detection and ranging, LeddarTech), a monocular camera, and rotational robotics to recover hemispherical, colored point clouds. This includes an entire framework of calibration and fusion algorithms utilizing Leddar depth measurements and image parallax information. The FSS was applied to scan a cottonwood (Populus spp.) stand repeatedly during autumnal leaf drop. Results show that the calibration error based on bundle adjustment is between 1 and 3 pixels. The FSS scans exhibit a similar canopy volume profile to the benchmarking terrestrial laser scans, with an r2 between 0.5 and 0.7 in varying stages of leaf cover. The 3D point distribution information from FSS also provides a valuable correction factor for the leaf area index (LAI) estimation. The consistency of corrected LAI measurement demonstrates the practical value of deploying FSS for canopy foliage monitoring.
关键词： terrestrial laser scanning,canopy monitoring,monocular camera,sensor fusion,LiDAR,Leddar,structure from motion,leaf area index
更新于2025-09-12 10:27:22
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Estimating Mangrove Forest Volume Using Terrestrial Laser Scanning and UAV-Derived Structure-from-Motion
摘要： Mangroves provide a variety of ecosystem services, which can be related to their structural complexity and ability to store carbon in the above ground biomass (AGB). Quantifying AGB in mangroves has traditionally been conducted using destructive, time-consuming, and costly methods, however, Structure-from-Motion Multi-View Stereo (SfM-MVS) combined with unmanned aerial vehicle (UAV) imagery may provide an alternative. Here, we compared the ability of SfM-MVS with terrestrial laser scanning (TLS) to capture forest structure and volume in three mangrove sites of differing stand age and species composition. We describe forest structure in terms of point density, while forest volume is estimated as a proxy for AGB using the surface differencing method. In general, SfM-MVS poorly captured mangrove forest structure, but was efficient in capturing the canopy height for volume estimations. The differences in volume estimations between TLS and SfM-MVS were higher in the juvenile age site (42.95%) than the mixed (28.23%) or mature (12.72%) age sites, with a higher stem density affecting point capture in both methods. These results can be used to inform non-destructive, cost-effective, and timely assessments of forest structure or AGB in mangroves in the future.
关键词： mangroves,terrestrial laser scanning,forest structure,structure-from-motion
更新于2025-09-11 14:15:04