Performance Evaluations for Super-Resolution Mosaicing on UAS Surveillance Videos

Camargo, Aldo; He, Qiang; Palaniappan, Kannappan

doi:10.5772/56534

Cited by 5 publications

(3 citation statements)

References 19 publications

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“…Figure 5 shows the locations that have been developed literature about UAS technology. The countries where the UAS has been prominently found literature is the United States of America (188), China (131) and Germany (52). For this reason, these countries might have addressed certain challenges and benefits of a successful implementation of UAS.…”

Section: E Location Of the Network Link Mapmentioning

confidence: 99%

Systematic Literature Research of the Current Implementation of Unmanned Aerial System (UAS) in the Construction Industry

2019

IJITEE

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The implementation of UAS is bringing easiness and time saving activities into the currently construction site task. In the construction industry, diverse and relevant benefits of the technology have been identified through the project life cycle, such as monitoring project progress report, faster and low-cost land measurements and 3D modelling. Currently, the most valuable benefits of the UAS in the construction industry are related to automation the construction process, low cost, greater speed and safer real-time data collection compare with the traditional methods, and a reliable replacement over satellites and manned vehicles in terms of high-resolution images. However, there is a lack of exemplification and clarity of the actual implementation of the UAS in the construction industry in terms of adoption process and impacted usage. Therefore, a systematic literature review was carried out in order to explore the literature available of the topic related to implementation of unmanned aerial system in the construction industry, the most relevant tasks, cases, areas of usage and the reasons of applying it. The finding of this paper is providing exemplification models of current usage such as visualisation and disaster management, evolution map of the UAS according to the publication numbers and construction project stages when to use the UAS.

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Section: E Location Of the Network Link Mapmentioning

confidence: 99%

Systematic Literature Research of the Current Implementation of Unmanned Aerial System (UAS) in the Construction Industry

2019

IJITEE

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“…Kalman filter is employed for smoothing operation. In [23], image operations are applied in the spatial domain, with an iterated projection in the background for Super-Resolution (SR) mosaic construction of low-resolution frames from UAV. In this paper, SIFT is used for computing initial SR mosaic, and three different methods namely: Steepest Descent method(fastest), Conjugate Gradient Method (visually best), and Levenberg-Marquardt algorithms are applied for non-linear optimization.…”

Section: Introductionmentioning

confidence: 99%

AirMatch: An Automated Mosaicing System with Video Preprocessing Engine for Multiple Aerial Feeds

Rasheed¹,

Qureshi²,

Khan³

et al. 2021

IEICE Trans. Inf. & Syst.

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Surveillance through aerial systems is in place for years. Such systems are expensive, and a large fleet is in operation around the world without upgrades. These systems have low resolution and multiple analog cameras on-board, with Digital Video Recorders (DVRs) at the control station. Generated digital videos have multi-scenes from multi-feeds embedded in a single video stream and lack video stabilization. Replacing on-board analog cameras with the latest digital counterparts requires huge investment. These videos require stabilization and other automated video analysis prepossessing steps before passing it to the mosaicing algorithm. Available mosaicing software are not tailored to segregate feeds from different cameras and scenes, automate image enhancements, and stabilize before mosaicing (image stitching). We present "AirMatch", a new automated system that first separates camera feeds and scenes, then stabilize and enhance the video feed of each camera; generates a mosaic of each scene of every feed and produce a super quality mosaic by stitching mosaics of all feeds. In our proposed solution, state-of-the-art video analytics techniques are tailored to work on videos from vintage cameras in aerial applications. Our new framework is independent of specialized hardware requirements and generates effective mosaics. Affine motion transform with smoothing Gaussian filter is selected for the stabilization of videos. A histogrambased method is performed for scene change detection and image contrast enhancement. Oriented FAST and rotated BRIEF (ORB) is selected for feature detection and descriptors in video stitching. Several experiments on a number of video streams are performed and the analysis shows that our system can efficiently generate mosaics of videos with high distortion and artifacts, compared with other commercially available mosaicing software.

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“…Stitching is the process of generating a larger image that joints the entirety of the overlapping images of an input video [1, 2]. Focusing on the special kind of video captured from an aerial platform, aerial video stitching [3–17] is a key component in various application fields, including disaster monitoring, aerial surveillance, remote sensing and UAV navigation, etc.…”

Section: Introductionmentioning

confidence: 99%

Fast Aerial Video Stitching

Yang

et al. 2014

International Journal of Advanced Robotic Systems

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The highly efficient and robust stitching of aerial video captured by unmanned aerial vehicles (UAVs) is a challenging problem in the field of robot vision. Existing commercial image stitching systems have seen success with offline stitching tasks, but they cannot guarantee high-speed performance when dealing with online aerial video sequences. In this paper, we present a novel system which has an unique ability to stitch high-frame rate aerial video at a speed of 150 frames per second (FPS). In addition, rather than using a high-speed vision platform such as FPGA or CUDA, our system is running on a normal personal computer. To achieve this, after the careful comparison of the existing invariant features, we choose the FAST corner and binary descriptor for efficient feature extraction and representation, and present a spatial and temporal coherent filter to fuse the UAV motion information into the feature matching. The proposed filter can remove the majority of feature correspondence outliers and significantly increase the speed of robust feature matching by up to 20 times. To achieve a balance between robustness and efficiency, a dynamic key frame-based stitching framework is used to reduce the accumulation errors. Extensive experiments on challenging UAV datasets demonstrate that our approach can break through the speed limitation and generate an accurate stitching image for aerial video stitching tasks.

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Performance Evaluations for Super-Resolution Mosaicing on UAS Surveillance Videos

Cited by 5 publications

References 19 publications

Systematic Literature Research of the Current Implementation of Unmanned Aerial System (UAS) in the Construction Industry

Systematic Literature Research of the Current Implementation of Unmanned Aerial System (UAS) in the Construction Industry

AirMatch: An Automated Mosaicing System with Video Preprocessing Engine for Multiple Aerial Feeds

Fast Aerial Video Stitching

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