Journal ArticleDOI
Evaluation of image-based modeling and laser scanning accuracy for emerging automated performance monitoring techniques
TLDR
An overview of the newly developed automated image-based reconstruction approach and exclusive features which distinct it from other image- based or conventional photogrammetric techniques is presented and the terrestrial laser scanning approach carried out for reconstruction and comparison of as-built scenes is presented.About:
This article is published in Automation in Construction.The article was published on 2011-12-01. It has received 333 citations till now. The article focuses on the topics: Point cloud & Visualization.read more
Citations
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Journal ArticleDOI
Building Information Modeling (BIM) for existing buildings — Literature review and future needs
TL;DR: Results show scarce BIM implementation in existing buildings yet, due to challenges of (1) high modeling/conversion effort from captured building data into semantic BIM objects, (2) updating of information in BIM and (3) handling of uncertain data, objects and relations in B IM occurring inexisting buildings.
Journal ArticleDOI
Mobile 3D mapping for surveying earthwork projects using an Unmanned Aerial Vehicle (UAV) system
Sebastian Siebert,Jochen Teizer +1 more
TL;DR: The performance evaluation of a UAV system that was built to rapidly and autonomously acquire mobile three-dimensional mapping data and its execution for the generation of 3D point clouds from digital mobile images is presented.
Journal ArticleDOI
Advances in Computer Vision-Based Civil Infrastructure Inspection and Monitoring
TL;DR: An overview of recent advances in computer vision techniques as they apply to the problem of civil infrastructure condition assessment and some of the key challenges that persist toward the goal of automated vision-based civil infrastructure and monitoring are presented.
Journal ArticleDOI
Research trends and opportunities of augmented reality applications in architecture, engineering, and construction
TL;DR: This paper discusses trends in AR applications for architecture, engineering, construction, and facility management (AEC/FM), and outlines the research trends and opportunities for applying AR in the fields of AEC/ FM.
Journal ArticleDOI
Computer vision techniques for construction safety and health monitoring
TL;DR: This paper categorizes previous studies into three groups-object detection, object tracking, and action recognition-based on types of information required to evaluate unsafe conditions and acts, and provides researchers insights into advancing knowledge and techniques for computer vision-based safety and health monitoring.
References
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Proceedings ArticleDOI
Modeling and rendering architecture from photographs: a hybrid geometry- and image-based approach
TL;DR: This work presents a new approach for modeling and rendering existing architectural scenes from a sparse set of still photographs, which combines both geometry-based and imagebased techniques, and presents view-dependent texture mapping, a method of compositing multiple views of a scene that better simulates geometric detail on basic models.
Journal ArticleDOI
An efficient solution to the five-point relative pose problem
TL;DR: The algorithm is used in a robust hypothesize-and-test framework to estimate structure and motion in real-time with low delay and is the first algorithm well-suited for numerical implementation that also corresponds to the inherent complexity of the problem.
Multiple View Geometry
Richard Hartley,Andrew Zisserman +1 more
TL;DR: A perspective (central) projection camera is represented by a matrix that can be computed from the correspondence of four (or more) points.
Journal ArticleDOI
Visual Modeling with a Hand-Held Camera
Marc Pollefeys,Luc Van Gool,Maarten Vergauwen,Frank Verbiest,Kurt Cornelis,Jan Tops,Reinhard Koch +6 more
TL;DR: A complete system to build visual models from camera images is presented and a combined approach with view-dependent geometry and texture is presented, as an application fusion of real and virtual scenes is also shown.
Proceedings ArticleDOI
Unsupervised Learning of Human Action Categories Using Spatial-Temporal Words.
TL;DR: The approach is not only able to classify different actions, but also to localize different actions simultaneously in a novel and complex video sequence.