Potential of big visual data and building information modeling for construction performance analytics: An exploratory study
Kevin Han,Mani Golparvar-Fard +1 more
TLDR
This paper investigates current strategies for leveraging emerging big visual data and BIM in construction performance monitoring from these three aspects, characterizes gaps in knowledge via case studies and structures a road map for research in visual sensing and analytics.About:
This article is published in Automation in Construction.The article was published on 2017-01-01 and is currently open access. It has received 160 citations till now. The article focuses on the topics: Visual analytics & Analytics.read more
Citations
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Towards a semantic Construction Digital Twin: directions for future research
TL;DR: The paper reviews the multi-faceted applications of BIM during the construction stage and highlights limits and requirements, paving the way to the concept of a Construction Digital Twin, described in terms of underpinning research themes, while elaborating on areas for future research.
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Construction with digital twin information systems
TL;DR: DTC should be viewed as a comprehensive mode of construction that prioritizes closing the control loops rather than an extension of BIM tools integrated with sensing and monitoring technologies.
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Computer Vision Techniques in Construction: A Critical Review
TL;DR: In this paper, the authors present a review of state-of-the-art methods in a typical vision-based scheme, and discuss challenges associated with their application, aiming to guide practitioners to find suitable approaches for a particular project.
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On-Demand Monitoring of Construction Projects through a Game-Like Hybrid Application of BIM and Machine Learning
Farzad Pour Rahimian,Farzad Pour Rahimian,Saleh Seyedzadeh,Stephen Oliver,Sergio Rodriguez,Nashwan Dawood +5 more
TL;DR: A framework and a proof of concept prototype for on-demand automated simulation of construction projects, integrating some cutting edge IT solutions, namely image processing, machine learning, BIM and Virtual Reality are presented.
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Combining inverse photogrammetry and BIM for automated labeling of construction site images for machine learning
Alexander Braun,André Borrmann +1 more
TL;DR: A novel method for automatically labeling construction images based on the combination of 4D Building Information Models and an inverse photogrammetry approach is presented, providing over 30,000 automatically labeled elements.
References
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Distinctive Image Features from Scale-Invariant Keypoints
TL;DR: This paper presents a method for extracting distinctive invariant features from images that can be used to perform reliable matching between different views of an object or scene and can robustly identify objects among clutter and occlusion while achieving near real-time performance.
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ImageNet Large Scale Visual Recognition Challenge
Olga Russakovsky,Jia Deng,Hao Su,Jonathan Krause,Sanjeev Satheesh,Sean Ma,Zhiheng Huang,Andrej Karpathy,Aditya Khosla,Michael S. Bernstein,Alexander C. Berg,Li Fei-Fei +11 more
TL;DR: The ImageNet Large Scale Visual Recognition Challenge (ILSVRC) as mentioned in this paper is a benchmark in object category classification and detection on hundreds of object categories and millions of images, which has been run annually from 2010 to present, attracting participation from more than fifty institutions.
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The Pascal Visual Object Classes (VOC) Challenge
TL;DR: The state-of-the-art in evaluated methods for both classification and detection are reviewed, whether the methods are statistically different, what they are learning from the images, and what the methods find easy or confuse.
Book
Multiple view geometry in computer vision
Richard Hartley,Andrew Zisserman +1 more
TL;DR: In this article, the authors provide comprehensive background material and explain how to apply the methods and implement the algorithms directly in a unified framework, including geometric principles and how to represent objects algebraically so they can be computed and applied.
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Closed-form solution of absolute orientation using unit quaternions
TL;DR: A closed-form solution to the least-squares problem for three or more paints is presented, simplified by use of unit quaternions to represent rotation.