scholarly journals Aircraft Pose Estimation Based on Geometry Structure Features and Line Correspondences

Sensors ◽  
2019 ◽  
Vol 19 (9) ◽  
pp. 2165 ◽  
Author(s):  
Xichao Teng ◽  
Qifeng Yu ◽  
Jing Luo ◽  
Gang Wang ◽  
Xiaohu Zhang
Keyword(s):  
Pose Estimation ◽  
Estimation Method ◽  
Bilateral Symmetry ◽  
3D Models ◽  
Parallel Line ◽  
Geometry Structure ◽  
Aerospace Applications ◽  
Vision Sensors ◽  
Structure Recognition ◽  
Established Line

A robust and accurate aircraft pose estimation method is proposed in this paper. The aircraft pose reflects the flight status of the aircraft and accurate pose measurement is of great importance in many aerospace applications. This work aims to establish a universal framework to estimate the aircraft pose based on generic geometry structure features. In our method, line features are extracted to describe the structure of an aircraft in single images and the generic geometry features are exploited to form line groups for aircraft structure recognition. Parallel line clustering is utilized to detect the fuselage reference line and bilateral symmetry property of aircraft provides an important constraint for the extraction of wing edge lines under weak perspective projection. After identifying the main structure of the aircraft, a planes intersection method is used to obtain the 3D pose parameters based on the established line correspondences. Our proposed method can increase the measuring range of binocular vision sensors and has the advantage of not relying on 3D models, cooperative marks or other feature datasets. Experimental results show that our method can obtain reliable and accurate pose information of different types of aircraft.

scholarly journals Pose Estimation for Straight Wing Aircraft Based on Consistent Line Clustering and Planes Intersection

Sensors ◽  
2019 ◽  
Vol 19 (2) ◽  
pp. 342 ◽  
Author(s):  
Xichao Teng ◽  
Qifeng Yu ◽  
Jing Luo ◽  
Xiaohu Zhang ◽  
Gang Wang
Keyword(s):  
Pose Estimation ◽  
Estimation Method ◽  
3D Models ◽  
Parallel Line ◽  
Long Distance ◽  
Point Matching ◽  
Aerospace Applications ◽  
Feature Point Matching ◽  
Line Features ◽  
Straight Wing

Aircraft pose estimation is a necessary technology in aerospace applications, and accurate pose parameters are the foundation for many aerospace tasks. In this paper, we propose a novel pose estimation method for straight wing aircraft without relying on 3D models or other datasets, and two widely separated cameras are used to acquire the pose information. Because of the large baseline and long-distance imaging, feature point matching is difficult and inaccurate in this configuration. In our method, line features are extracted to describe the structure of straight wing aircraft in images, and pose estimation is performed based on the common geometry constraints of straight wing aircraft. The spatial and length consistency of the line features is used to exclude irrelevant line segments belonging to the background or other parts of the aircraft, and density-based parallel line clustering is utilized to extract the aircraft’s main structure. After identifying the orientation of the fuselage and wings in images, planes intersection is used to estimate the 3D localization and attitude of the aircraft. Experimental results show that our method estimates the aircraft pose accurately and robustly.

scholarly journals TOWARDS AN ACCURATE LOW-COST STEREO-BASED NAVIGATION OF UNMANNED PLATFORMS IN GNSS-DENIED AREAS

2019 ◽  
Vol XLII-2/W17 ◽  
pp. 323-329
Author(s):  
Z. Shtain ◽  
S. Filin
Keyword(s):  
Pose Estimation ◽  
Inertial Sensors ◽  
Low Cost ◽  
Estimation Method ◽  
Slight Modification ◽  
Bundle Adjustment ◽  
Positional Accuracy ◽  
Accurate Localization ◽  
Vision Sensors ◽  
System Configurations

Abstract. While lightweight stereo vision sensors provide detailed and high-resolution information that allows robust and accurate localization, the computation demands required for such process is doubled compared to monocular sensors. In this paper, an alternative model for pose estimation of stereo sensors is introduced which provides an efficient and precise framework for investigating system configurations and maximize pose accuracies. Using the proposed formulation, we examine the parameters that affect accurate pose estimation and their magnitudes and show that for standard operational altitudes of ∼50 m, a five-fold improvement in localization is reached, from ∼0.4–0.5 m with a single sensor to less than 0.1 m by taking advantage of the extended field of view from both cameras. Furthermore, such improvement is reached using cameras with reduced sensor size which are more affordable. Hence, a dual-camera setup improves not only the pose estimation but also enables to use smaller sensors and reduce the overall system cost. Our analysis shows that even a slight modification in camera directions improves the positional accuracy further and yield attitude angle as accurate as ±6’ (compared to ±20’). The proposed pose estimation method relieves computational demands of traditional bundle adjustment processes and is easily integrated with other inertial sensors.

scholarly journals A New Multi-Person Pose Estimation Method Using the Partitioned CenterPose Network

2021 ◽  
Vol 11 (9) ◽  
pp. 4241
Author(s):  
Jiahua Wu ◽  
Hyo Jong Lee
Keyword(s):  
Pose Estimation ◽  
Human Body ◽  
State Of The Art ◽  
Estimation Method ◽  
Bottom Up ◽  
Center Point ◽  
Novel Approach ◽  
Body Joints

In bottom-up multi-person pose estimation, grouping joint candidates into the appropriately structured corresponding instance of a person is challenging. In this paper, a new bottom-up method, the Partitioned CenterPose (PCP) Network, is proposed to better cluster the detected joints. To achieve this goal, we propose a novel approach called Partition Pose Representation (PPR) which integrates the instance of a person and its body joints based on joint offset. PPR leverages information about the center of the human body and the offsets between that center point and the positions of the body’s joints to encode human poses accurately. To enhance the relationships between body joints, we divide the human body into five parts, and then, we generate a sub-PPR for each part. Based on this PPR, the PCP Network can detect people and their body joints simultaneously, then group all body joints according to joint offset. Moreover, an improved l1 loss is designed to more accurately measure joint offset. Using the COCO keypoints and CrowdPose datasets for testing, it was found that the performance of the proposed method is on par with that of existing state-of-the-art bottom-up methods in terms of accuracy and speed.

scholarly journals RobotP: A Benchmark Dataset for 6D Object Pose Estimation

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1299
Author(s):  
Honglin Yuan ◽  
Tim Hoogenkamp ◽  
Remco C. Veltkamp
Keyword(s):  
Pose Estimation ◽  
Ground Truth ◽  
3D Models ◽  
Depth Image ◽  
Great Success ◽  
Estimation Algorithms ◽  
Depth Images ◽  
Object Pose Estimation ◽  
Image Pairs ◽  
Bounding Boxes

Deep learning has achieved great success on robotic vision tasks. However, when compared with other vision-based tasks, it is difficult to collect a representative and sufficiently large training set for six-dimensional (6D) object pose estimation, due to the inherent difficulty of data collection. In this paper, we propose the RobotP dataset consisting of commonly used objects for benchmarking in 6D object pose estimation. To create the dataset, we apply a 3D reconstruction pipeline to produce high-quality depth images, ground truth poses, and 3D models for well-selected objects. Subsequently, based on the generated data, we produce object segmentation masks and two-dimensional (2D) bounding boxes automatically. To further enrich the data, we synthesize a large number of photo-realistic color-and-depth image pairs with ground truth 6D poses. Our dataset is freely distributed to research groups by the Shape Retrieval Challenge benchmark on 6D pose estimation. Based on our benchmark, different learning-based approaches are trained and tested by the unified dataset. The evaluation results indicate that there is considerable room for improvement in 6D object pose estimation, particularly for objects with dark colors, and photo-realistic images are helpful in increasing the performance of pose estimation algorithms.

Non-iterative pose estimation method based on the polarization information via a parallelogram

Measurement ◽  
2022 ◽  
Vol 187 ◽  
pp. 110274
Author(s):  
Zhang Zimiao ◽  
Xu kai ◽  
Wu Yanan ◽  
Zhang Shihai
Keyword(s):  
Pose Estimation ◽  
Estimation Method

Accurate O(n) pose estimation method using both lines and points

Optik ◽  
2016 ◽  
Vol 127 (19) ◽  
pp. 7875-7880
Author(s):  
Meng Li ◽  
Derong Chen ◽  
Jiulu Gong ◽  
Changyuan Wang
Keyword(s):  
Pose Estimation ◽  
Estimation Method
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