High Definition Corridor Mapping From Images Sequences

2020 ◽  
Vol 9 (1) ◽  
pp. 22-35
Author(s):  
Mert Gurturk ◽  
Yalçın Yılmaz ◽  
Baris Suleymanoglu ◽  
Arzu Soycan ◽  
Metin Soycan
Keyword(s):  
Autonomous Vehicles ◽  
Low Cost ◽  
Road Surface ◽  
High Definition ◽  
Intelligence Studies ◽  
Technological Developments ◽  
Vehicle Technology ◽  
Imaging Sensors ◽  
Mobile Mapping Systems ◽  
Mapping Systems

The density, high accuracy, and rapid collection of geographical data for road surface and surrounding objects and the extraction of meaningful information from these data increases its importance in line with technological developments. Artificial intelligence studies and developments in cloud technology have affected the automotive industry as well as every sector and have enabled the development of driverless vehicle technology. In order to safely drive with autonomous vehicles, high definition maps that contain detailed information for road surface and its surrounding objects with high precision at centimeter-level must be used. In this context, in recent years, the development of mobile mapping systems (MMS) consisting of low-cost sensors and the development of algorithms for the evaluation of the data obtained from these systems have become increasingly popular. In this study, it was investigated whether HD maps can be obtained by using low-cost imaging sensors.

scholarly journals Smartphones Based Mobile Mapping Systems

2014 ◽  
Vol XL-5 ◽  
pp. 29-34 ◽  
Author(s):  
A. Al-Hamad ◽  
N. El-Sheimy
Keyword(s):  
Mobile Phones ◽  
Spatial Data ◽  
Inertial Sensors ◽  
Low Cost ◽  
Micro Electro Mechanical System ◽  
Mobile Mapping ◽  
Moving Platforms ◽  
Gis Applications ◽  
Mobile Mapping Systems ◽  
Mapping Systems

The past 20 years have witnessed an explosive growth in the demand for geo-spatial data. This demand has numerous sources and takes many forms; however, the net effect is an ever-increasing thirst for data that is more accurate, has higher density, is produced more rapidly, and is acquired less expensively. For mapping and Geographic Information Systems (GIS) projects, this has been achieved through the major development of Mobile Mapping Systems (MMS). MMS integrate various navigation and remote sensing technologies which allow mapping from moving platforms (e.g. cars, airplanes, boats, etc.) to obtain the 3D coordinates of the points of interest. Such systems obtain accuracies that are suitable for all but the most demanding mapping and engineering applications. However, this accuracy doesn't come cheaply. As a consequence of the platform and navigation and mapping technologies used, even an "inexpensive" system costs well over 200 000 USD. Today's mobile phones are getting ever more sophisticated. Phone makers are determined to reduce the gap between computers and mobile phones. Smartphones, in addition to becoming status symbols, are increasingly being equipped with extended Global Positioning System (GPS) capabilities, Micro Electro Mechanical System (MEMS) inertial sensors, extremely powerful computing power and very high resolution cameras. Using all of these components, smartphones have the potential to replace the traditional land MMS and portable GPS/GIS equipment. This paper introduces an innovative application of smartphones as a very low cost portable MMS for mapping and GIS applications.

scholarly journals Novel low-cost mobile mapping systems for forest inventories as terrestrial laser scanning alternatives

2021 ◽  
Vol 104 ◽  
pp. 102512
Author(s):  
Martin Mokroš ◽  
Tomáš Mikita ◽  
Arunima Singh ◽  
Julián Tomaštík ◽  
Juliána Chudá ◽  
...  
Keyword(s):  
Laser Scanning ◽  
Low Cost ◽  
Terrestrial Laser Scanning ◽  
Mobile Mapping ◽  
Forest Inventories ◽  
Mobile Mapping Systems ◽  
Mapping Systems

scholarly journals Mobile Mapping Technologies

2021 ◽  
pp. 439-465
Author(s):  
Kai Wei Chiang ◽  
Guang-Je Tsai ◽  
Jhih Cing Zeng
Keyword(s):  
Sensor Fusion ◽  
Disaster Response ◽  
Autonomous Systems ◽  
High Definition ◽  
Mobile Mapping ◽  
Potential Applications ◽  
Historic Development ◽  
Mobile Mapping Systems ◽  
Indoor And Outdoor ◽  
Mapping Systems

AbstractThis chapter introduces the historic development as well as the latest progress of mobile mapping systems. First, mobile mapping technologies, including the introduction of positioning and mapping sensors, and how they can be integrated together, are briefly reviewed. Then the development of land-based, aerial, marine, and mobile portable mapping platforms is presented. The latest progress in mobile-mapping technologies is further discussed, along with sensor fusion schemes, seamless indoor and outdoor mapping strategies, and disaster response applications. In addition, this chapter explores future and potential applications, such as high-definition (HD) maps and autonomous mapping with autonomous systems.

scholarly journals Towards High-Definition 3D Urban Mapping: Road Feature-Based Registration of Mobile Mapping Systems and Aerial Imagery

2017 ◽  
Vol 9 (10) ◽  
pp. 975 ◽  
Author(s):  
Mahdi Javanmardi ◽  
Ehsan Javanmardi ◽  
Yanlei Gu ◽  
Shunsuke Kamijo
Keyword(s):  
Aerial Imagery ◽  
High Definition ◽  
Mobile Mapping ◽  
Feature Based ◽  
Urban Mapping ◽  
Mobile Mapping Systems ◽  
Mapping Systems

scholarly journals Multiple-Exposure Image Fusion for HDR Image Synthesis Using Learned Analysis Transformations

2019 ◽  
Vol 5 (3) ◽  
pp. 32 ◽  
Author(s):  
Ioannis Merianos ◽  
Nikolaos Mitianoudis
Keyword(s):  
Image Fusion ◽  
Dynamic Range ◽  
Low Cost ◽  
Image Synthesis ◽  
Range Image ◽  
Multiple Exposure ◽  
High Definition ◽  
Fusion Algorithm ◽  
Exposure Fusion ◽  
Imaging Sensors

Modern imaging applications have increased the demand for High-Definition Range (HDR) imaging. Nonetheless, HDR imaging is not easily available with low-cost imaging sensors, since their dynamic range is rather limited. A viable solution to HDR imaging via low-cost imaging sensors is the synthesis of multiple-exposure images. A low-cost sensor can capture the observed scene at multiple-exposure settings and an image-fusion algorithm can combine all these images to form an increased dynamic range image. In this work, two image-fusion methods are combined to tackle multiple-exposure fusion. The luminance channel is fused using the Mitianoudis and Stathaki (2008) method, while the color channels are combined using the method proposed by Mertens et al. (2007). The proposed fusion algorithm performs well without halo artifacts that exist in other state-of-the-art methods. This paper is an extension version of a conference, with more analysis on the derived method and more experimental results that confirm the validity of the method.

scholarly journals An ISVD-based Euclidian structure from motion for smartphones

2014 ◽  
Vol XL-5 ◽  
pp. 401-406 ◽  
Author(s):  
A. Masiero ◽  
A. Guarnieri ◽  
A. Vettore ◽  
F. Pirotti
Keyword(s):  
3D Reconstruction ◽  
Mobile Devices ◽  
Structure From Motion ◽  
Computationally Efficient ◽  
Mobile Mapping ◽  
Reconstruction Procedure ◽  
Value Decomposition ◽  
Imaging Sensors ◽  
Mobile Mapping Systems ◽  
Mapping Systems

The development of Mobile Mapping systems over the last decades allowed to quickly collect georeferenced spatial measurements by means of sensors mounted on mobile vehicles. Despite the large number of applications that can potentially take advantage of such systems, because of their cost their use is currently typically limited to certain specialized organizations, companies, and Universities. However, the recent worldwide diffusion of powerful mobile devices typically embedded with GPS, Inertial Navigation System (INS), and imaging sensors is enabling the development of small and compact mobile mapping systems.<br><br> More specifically, this paper considers the development of a 3D reconstruction system based on photogrammetry methods for smartphones (or other similar mobile devices). The limited computational resources available in such systems and the users' request for real time reconstructions impose very stringent requirements on the computational burden of the 3D reconstruction procedure.<br><br> This work takes advantage of certain recently developed mathematical tools (incremental singular value decomposition) and of photogrammetry techniques (structure from motion, Tomasi–Kanade factorization) to access very computationally efficient Euclidian 3D reconstruction of the scene.<br><br> Furthermore, thanks to the presence of instrumentation for localization embedded in the device, the obtained 3D reconstruction can be properly georeferenced.

scholarly journals A low-cost wireless endoscope camera: a preliminary report

2021 ◽  
Vol 27 (1) ◽  
Author(s):  
J. M. Lazarus ◽  
M. Ncube
Keyword(s):  
Minimally Invasive Surgery ◽  
Minimally Invasive ◽  
Video Transmission ◽  
Low Cost ◽  
Battery Life ◽  
Resource Constrained ◽  
High Definition ◽  
Industry Standard ◽  
Constrained Environments ◽  
The Cost

Abstract Background Technology currently used for surgical endoscopy was developed and is manufactured in high-income economies. The cost of this equipment makes technology transfer to resource constrained environments difficult. We aimed to design an affordable wireless endoscope to aid visualisation during rigid endoscopy and minimally invasive surgery (MIS). The initial prototype aimed to replicate a 4-mm lens used in rigid cystoscopy. Methods Focus was placed on using open-source resources to develop the wireless endoscope to significantly lower the cost and make the device accessible for resource-constrained settings. An off the shelf miniature single-board computer module was used because of its low cost (US$10) and its ability to handle high-definition (720p) video. Open-source Linux software made monitor mode (“hotspot”) wireless video transmission possible. A 1280 × 720 pixel high-definition tube camera was used to generate the video signal. Video is transmitted to a standard laptop computer for display. Bench testing included latency of wireless digital video transmission. Comparison to industry standard wired cameras was made including weight and cost. The battery life was also assessed. Results In comparison with industry standard cystoscope lens, wired camera, video processing unit and light source, the prototype costs substantially less. (US$ 230 vs 28 000). The prototype is light weight (184 g), has no cables tethering and has acceptable battery life (of over 2 h, using a 1200 mAh battery). The camera transmits video wirelessly in near real time with only imperceptible latency of < 200 ms. Image quality is high definition at 30 frames per second. Colour rendering is good, and white balancing is possible. Limitations include the lack of a zoom. Conclusion The novel wireless endoscope camera described here offers equivalent high-definition video at a markedly reduced cost to contemporary industry wired units and could contribute to making minimally invasive surgery possible in resource-constrained environments.

scholarly journals CNN-Based Road-Surface Crack Detection Model That Responds to Brightness Changes

Electronics ◽  
2021 ◽  
Vol 10 (12) ◽  
pp. 1402
Author(s):  
Taehee Lee ◽  
Yeohwan Yoon ◽  
Chanjun Chun ◽  
Seungki Ryu
Keyword(s):  
Surface Crack ◽  
Autonomous Vehicles ◽  
Crack Detection ◽  
Model Performance ◽  
Semantic Segmentation ◽  
Road Surface ◽  
Image Brightness ◽  
The Road ◽  
Detection Model ◽  
Artificial Intelligence Models

Poor road-surface conditions pose a significant safety risk to vehicle operation, especially in the case of autonomous vehicles. Hence, maintenance of road surfaces will become even more important in the future. With the development of deep learning-based computer image processing technology, artificial intelligence models that evaluate road conditions are being actively researched. However, as the lighting conditions of the road surface vary depending on the weather, the model performance may degrade for an image whose brightness falls outside the range of the learned image, even for the same road. In this study, a semantic segmentation model with an autoencoder structure was developed for detecting road surface along with a CNN-based image preprocessing model. This setup ensures better road-surface crack detection by adjusting the image brightness before it is input into the road-crack detection model. When the preprocessing model was applied, the road-crack segmentation model exhibited consistent performance even under varying brightness values.

scholarly journals Auction-Based Consensus of Autonomous Vehicles for Multi-Target Dynamic Task Allocation and Path Planning in an Unknown Obstacle Environment

2021 ◽  
Vol 11 (11) ◽  
pp. 5057
Author(s):  
Wan-Yu Yu ◽  
Xiao-Qiang Huang ◽  
Hung-Yi Luo ◽  
Von-Wun Soo ◽  
Yung-Lung Lee
Keyword(s):  
Path Planning ◽  
Task Allocation ◽  
Autonomous Vehicles ◽  
Autonomous Vehicle ◽  
Dynamic Task ◽  
The Core ◽  
Dynamic Task Allocation ◽  
Vehicle Technology ◽  
Future Work ◽  
Complicated Task

The autonomous vehicle technology has recently been developed rapidly in a wide variety of applications. However, coordinating a team of autonomous vehicles to complete missions in an unknown and changing environment has been a challenging and complicated task. We modify the consensus-based auction algorithm (CBAA) so that it can dynamically reallocate tasks among autonomous vehicles that can flexibly find a path to reach multiple dynamic targets while avoiding unexpected obstacles and staying close as a group as possible simultaneously. We propose the core algorithms and simulate with many scenarios empirically to illustrate how the proposed framework works. Specifically, we show that how autonomous vehicles could reallocate the tasks among each other in finding dynamically changing paths while certain targets may appear and disappear during the movement mission. We also discuss some challenging problems as a future work.

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