Optimized selection of key frames for monocular videogrammetric surveying of civil infrastructure

Videogrammetry is an inexpensive and easy-to-use technology for spatial 3D scene recovery. When applied to large scale civil infrastructure scenes, only a small percentage of the collected video frames are required to achieve robust results. However, choosing the right frames requires careful consideration. Videotaping a built infrastructure scene results in large video files filled with blurry, noisy, or redundant frames. This is due to frame rate to camera speed ratios that are often higher than necessary; camera and lens imperfections and limitations that result in imaging noise; and occasional jerky motions of the camera that result in motion blur; all of which can significantly affect the performance of the videogrammetric pipeline. To tackle these issues, this paper proposes a novel method for automating the selection of an optimized number of informative, high quality frames. According to this method, as the first step, blurred frames are removed using the thresholds determined based on a minimum level of frame quality required to obtain robust results. Then, an optimum number of key frames are selected from the remaining frames using the selection criteria devised by the authors. Experimental results show that the proposed method outperforms existing methods in terms of improved 3D reconstruction results, while maintaining the optimum number of extracted frames needed to generate high quality 3D point clouds.© 2012 Elsevier Ltd. All rights reserved.

Design methodology for composite structures: A small low air-speed wind turbine blade case study

A small low air-speed wind turbine blade case study is used to demonstrate the effectiveness of a materials and design selection methodology described by Monroy Aceves et al. (2008) [24] for composite structures. The blade structure comprises a shell of uniform thickness and a unidirectional reinforcement. The shell outer geometry is fixed by aerodynamic considerations. A wide range of lay-ups are considered for the shell and reinforcement. Structural analysis is undertaken using the finite element method. Results are incorporated into a database for analysis using material selection software. A graphical selection stage is used to identify the lightest blade meeting appropriate design constraints. The proposed solution satisfies the design requirements and improves on the prototype benchmark by reducing the mass by almost 50%. The flexibility of the selection software in allowing identification of trends in the results and modifications to the selection criteria is demonstrated. Introducing a safety factor of two on the material failure stresses increases the mass by only 11%. The case study demonstrates that the proposed design methodology is useful in preliminary design where a very wide range of cases should be considered using relatively simple analysis. © 2011 Elsevier Ltd.

Part I: Binders & technologies - Basic principles

The first three reports in this series (Parts I, II and III) deals with binders and technologies used in stabilisation/ solidification (S/S) practice and research in the UK. This first part covers 'basic principles'while the second covers 'research' and the third 'applications'. The purpose of this work, which forms part of the Network STARNET on stabilisation/solidification treatment and remediation, is to identify the knowledge gaps and future research needs in this field. This paper describes the details and basic principles of available binders and technologies in the UK. The introduction in the report includes background on S/S, legislation aspects, overview of STARNET and its activities and details of commonly used binder selection criteria. The report is then divided into two main sections. The first covers binders and includes cement, blastfurnace slag, pulverised fuel ash, lime, natural and organophilic clays, bitumen, waste binders and concludes with proprietary binders. The second part details implementation processes for S/S treatment systems starting with ex-situ treatment systems, such as plant processing, direct mixing and in-drum processing and finishes with in-situ treatment processes, such as mechanical mixing and pressure mixing. © 2005 Taylor & Francis Group.

Generating the Sparse Point Cloud of a Civil Infrastructure Scene Using a Single Video Camera under Practical Constraints

Automating the model generation process of infrastructure can substantially reduce the modeling time and cost. This paper presents a method to generate a sparse point cloud of an infrastructure scene using a single video camera under practical constraints. It is the first step towards establishing an automatic framework for object-oriented as-built modeling. Motion blur and key frame selection criteria are considered. Structure from motion and bundle adjustment are explored. The method is demonstrated in a case study where the scene of a reinforced concrete bridge is videotaped, reconstructed, and metrically validated. The result indicates the applicability, efficiency, and accuracy of the proposed method.

Multi-criteria material selection in engineering design

Almost all material selection problems require that a compromise be sought between some metric of performance and cost. Trade-off methods using utility functions allow optimal solutions to be found for two objective, but for three it is harder. This paper develops and demonstrates a method for dealing with three objectives.

Neuro-Fuzzy genetic system for selection of construction project managers

Choosing a project manager for a construction project—particularly, large projects—is a critical project decision. The selection process involves different criteria and should be in accordance with company policies and project specifications. Traditionally, potential candidates are interviewed and the most qualified are selected in compliance with company priorities and project conditions. Precise computing models that could take various candidates’ information into consideration and then pinpoint the most qualified person with a high degree of accuracy would be beneficial. On the basis of the opinions of experienced construction company managers, this paper, through presenting a fuzzy system, identifies the important criteria in selecting a project manager. The proposed fuzzy system is based on IF-THEN rules; a genetic algorithm improves the overall accuracy as well as the functions used by the fuzzy system to make initial estimates of the cluster centers for fuzzy c-means clustering. Moreover, a back-propagation neutral network method was used to train the system. The optimal measures of the inference parameters were identified by calculating the system’s output error and propagating this error within the system. After specifying the system parameters, the membership function parameters—which by means of clustering and projection were approximated—were tuned with the genetic algorithm. Results from this system in selecting project managers show its high capability in making high-quality personnel predictions