scholarly journals On the Benefits of Color Information for Feature Matching in Outdoor Environments

Robotics ◽  
2020 ◽  
Vol 9 (4) ◽  
pp. 85
Author(s):  
Annika Hoffmann
Keyword(s):  
Feature Detection ◽  
Feature Matching ◽  
Robot Navigation ◽  
Navigation Systems ◽  
Color Information ◽  
Basic Technique ◽  
Outdoor Environments ◽  
Matching Performance ◽  
Indoor And Outdoor Environments ◽  
Indoor And Outdoor

The detection and description of features is one basic technique for many visual robot navigation systems in both indoor and outdoor environments. Matched features from two or more images are used to solve navigation problems, e.g., by establishing spatial relationships between different poses in which the robot captured the images. Feature detection and description is particularly challenging in outdoor environments, and widely used grayscale methods lead to high numbers of outliers. In this paper, we analyze the use of color information for keypoint detection and description. We consider grayscale and color-based detectors and descriptors, as well as combinations of them, and evaluate their matching performance. We demonstrate that the use of color information for feature detection and description markedly increases the matching performance.

scholarly journals Survey of Radio Navigation Systems

2015 ◽  
Vol 61 (1) ◽  
pp. 43-48 ◽  
Author(s):  
Przemysław Gilski ◽  
Jacek Stefański
Keyword(s):  
Information Processing ◽  
Navigation Systems ◽  
Consumer Behavior Analysis ◽  
Radio Navigation ◽  
Pedestrian Navigation ◽  
Outdoor Environments ◽  
Wireless Positioning ◽  
Indoor And Outdoor Environments ◽  
Processing Mechanisms ◽  
Indoor And Outdoor

Abstract At present, there is a growing demand for radio navigation systems, ranging from pedestrian navigation to consumer behavior analysis. These systems have been successfully used in many applications and have become very popular in recent years. In this paper we present a review of selected wireless positioning solutions operating in both indoor and outdoor environments. We describe different positioning techniques, methods, systems, as well as information processing mechanisms

scholarly journals Multifeature Image Indexing for Robot Localization in Textureless Environments

Robotics ◽  
2019 ◽  
Vol 8 (2) ◽  
pp. 37
Author(s):  
Tran Duc Dung ◽  
Delowar Hossain ◽  
Shin-ichiro Kaneko ◽  
Genci Capi
Keyword(s):  
Image Matching ◽  
Robot Navigation ◽  
Image Indexing ◽  
Mobile Robot Navigation ◽  
Depth Information ◽  
Robot Localization ◽  
Histogram Of Oriented Gradients ◽  
Outdoor Environments ◽  
Indoor And Outdoor Environments ◽  
Indoor And Outdoor

Robot localization is an important task for mobile robot navigation. There are many methods focused on this issue. Some methods are implemented in indoor and outdoor environments. However, robot localization in textureless environments is still a challenging task. This is because in these environments, the scene appears the same in almost every position. In this work, we propose a method that can localize robots in textureless environments. We use Histogram of Oriented Gradients (HOG) and Speeded Up Robust Feature (SURF) descriptors together with Depth information to form a Depth-HOG-SURF multifeature descriptor, which is later used for image matching. K-means clustering is applied to partition the whole feature into groups that are collectively called visual vocabulary. All the images in the database are encoded using the vocabulary. The experimental results show a good performance of the proposed method.

scholarly journals Three-Dimensional Reconstruction of Indoor and Outdoor Environments Using a Stereo Catadioptric System

2020 ◽  
Vol 10 (24) ◽  
pp. 8851
Author(s):  
Diana-Margarita Córdova-Esparza ◽  
Juan Terven ◽  
Julio-Alejandro Romero-González ◽  
Alfonso Ramírez-Pedraza
Keyword(s):  
Feature Matching ◽  
Three Dimensional ◽  
Ccd Camera ◽  
Outdoor Environments ◽  
Stereo Reconstruction ◽  
Dimensional Reconstruction ◽  
In The Wild ◽  
Epipolar Constraints ◽  
Indoor And Outdoor Environments ◽  
Indoor And Outdoor

In this work, we present a panoramic 3D stereo reconstruction system composed of two catadioptric cameras. Each one consists of a CCD camera and a parabolic convex mirror that allows the acquisition of catadioptric images. We describe the calibration approach and propose the improvement of existing deep feature matching methods with epipolar constraints. We show that the improved matching algorithm covers more of the scene than classic feature detectors, yielding broader and denser reconstructions for outdoor environments. Our system can also generate accurate measurements in the wild without large amounts of data used in deep learning-based systems. We demonstrate the system’s feasibility and effectiveness as a practical stereo sensor with real experiments in indoor and outdoor environments.

scholarly journals A Hybrid Framework for Mitigating Heading Drift for a Wearable Pedestrian Navigation System through Adaptive Fusion of Inertial and Magnetic Measurements

2021 ◽  
Vol 11 (4) ◽  
pp. 1902
Author(s):  
Liqiang Zhang ◽  
Yu Liu ◽  
Jinglin Sun
Keyword(s):  
Magnetic Measurements ◽  
Inertial Sensor ◽  
Angular Rate ◽  
Human Motion ◽  
Navigation Systems ◽  
Pedestrian Navigation ◽  
Hybrid Framework ◽  
Outdoor Environments ◽  
Adaptive Fusion ◽  
Indoor And Outdoor Environments

Pedestrian navigation systems could serve as a good supplement for other navigation methods or for extending navigation into areas where other navigation systems are invalid. Due to the accumulation of inertial sensing errors, foot-mounted inertial-sensor-based pedestrian navigation systems (PNSs) suffer from drift, especially heading drift. To mitigate heading drift, considering the complexity of human motion and the environment, we introduce a novel hybrid framework that integrates a foot-state classifier that triggers the zero-velocity update (ZUPT) algorithm, zero-angular-rate update (ZARU) algorithm, and a state lock, a magnetic disturbance detector, a human-motion-classifier-aided adaptive fusion module (AFM) that outputs an adaptive heading error measurement by fusing heuristic and magnetic algorithms rather than simply switching them, and an error-state Kalman filter (ESKF) that estimates the optimal systematic error. The validation datasets include a Vicon loop dataset that spans 324.3 m in a single room for approximately 300 s and challenging walking datasets that cover large indoor and outdoor environments with a total distance of 12.98 km. A total of five different frameworks with different heading drift correction methods, including the proposed framework, were validated on these datasets, which demonstrated that our proposed ZUPT–ZARU–AFM–ESKF-aided PNS outperforms other frameworks and clearly mitigates heading drift.

scholarly journals Health Effects and Exposure Assessment to Bioaerosols in Indoor and Outdoor Environments

Atmosphere ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 359
Author(s):  
Ewa Brągoszewska
Keyword(s):  
Exposure Assessment ◽  
Health Effects ◽  
Special Issue ◽  
Outdoor Environments ◽  
Indoor And Outdoor Environments ◽  
Indoor And Outdoor

The Atmosphere Special Issue entitled “Health Effects and Exposure Assessment to Bioaerosols in Indoor and Outdoor Environments” comprises five original papers [...]

Sign in / Sign up

Export Citation Format

Share Document