Visual Pattern Recognition Models for Remote Sensing of Civil Infrastructure

As-built models have been proven useful in many project-related applications, such as progress monitoring and quality control. However, they are not widely produced in most projects because a lot of effort is still necessary to manually convert remote sensing data from photogrammetry or laser scanning to an as-built model. In order to automate the generation of as-built models, the first and fundamental step is to automatically recognize infrastructure-related elements from the remote sensing data. This paper outlines a framework for creating visual pattern recognition models that can automate the recognition of infrastructure-related elements based on their visual features. The framework starts with identifying the visual characteristics of infrastructure element types and numerically representing them using image analysis tools. The derived representations, along with their relative topology, are then used to form element visual pattern recognition (VPR) models. So far, the VPR models of four infrastructure-related elements have been created using the framework. The high recognition performance of these models validates the effectiveness of the framework in recognizing infrastructure-related elements.

Initializing Vision Based Trackers Using Semantic Texton Forests

Vision based tracking can provide the spatial location of project related entities such as equipment, workers, and materials in a large-scale congested construction site. It tracks entities in a video stream by inferring their motion. To initiate the process, it is required to determine the pixel areas of the entities to be tracked in the following consecutive video frames. For the purpose of fully automating the process, this paper presents an automated way of initializing trackers using Semantic Texton Forests (STFs) method. STFs method performs simultaneously the segmentation of the image and the classification of the segments based on the low-level semantic information and the context information. In this paper, STFs method is tested in the case of wheel loaders recognition. In the experiments, wheel loaders are further divided into several parts such as wheels and body parts to help learn the context information. The results show 79% accuracy of recognizing the pixel areas of the wheel loader. These results signify that STFs method has the potential to automate the initialization process of vision based tracking.

Detection of Construction Workers in Video Frames for Automatic Initialization of Vision Trackers

Vision based tracking can provide the spatial location of construction entities such as equipment, workers, and materials in large scale, congested construction sites. It tracks entities in video streams by inferring their locations based on the entities’ visual features and motion histories. To initiate the process, it is necessary to determine the pixel areas corresponding to the construction entities to be tracked in the following consecutive video frames. In order to fully automate the process, an automated way of initialization is needed. This paper presents the method for construction worker detection which can automatically recognize and localize construction workers in video frames. The method first finds the foreground areas of moving objects using a background subtraction method. Within these foreground areas, construction workers are recognized based on the histogram of oriented gradients (HOG) and histogram of the HSV colors. HOG’s have proved to work effectively for detection of people, and the histogram of HSV colors helps differentiate between pedestrians and construction workers wearing safety vests. Preliminary experiments show that the proposed method has the potential to automate the initialization process of vision based tracking.

Achievements and Challenges in Recognizing and Reconstructing Civil Infrastructure

The US National Academy of Engineering recently identified restoring and improving urban infrastructure as one of the grand challenges of engineering. Part of this challenge stems from the lack of viable methods to map/label existing infrastructure. For computer vision, this challenge becomes “How can we automate the process of extracting geometric, object oriented models of infrastructure from visual data?” Object recognition and reconstruction methods have been successfully devised and/or adapted to answer this question for small or linear objects (e.g. columns). However, many infrastructure objects are large and/or planar without significant and distinctive features, such as walls, floor slabs, and bridge decks. How can we recognize and reconstruct them in a 3D model? In this paper, strategies for infrastructure object recognition and reconstruction are presented, to set the stage for posing the question above and discuss future research in featureless, large/planar object recognition and modeling.

Travel behaviour applied in freight transportation using intelligent products

The route planning problem for an order in freight transportation involves the selection of the best route for its transportation given a set of options that the network can offer. In its adaptive (or dynamic) version, the problem deals with the planning of a new route for an order while it is actually in transit typically because part or all of its pre-selected route is blocked or disrupted. In the intelligent product approach we are proposing, an order would be capable of identifying and evaluating such new routes in an automated manner and choosing the most preferable one without the intervention of humans. Because such approaches seek to mirror (and then automate) human decision making, in this paper we seek to identify new ways for dynamic route planning in industrial logistics inspired by the way people make similar decisions about their journey when they travel in multi-modal networks. We propose a new simulation game as a methodological tool for capturing their travel behaviour and we use it in this study. The results show that a simulation game can be used for capturing strategies and tactics of travellers and that intelligent products can provide a proper platform for the usage of such strategies in freight logistics. © 2012 IEEE.

Anti-counterfeiting and supply chain security

Counterfeit trade developed into a severe problem for many industries. While established security features such as holograms, micro printings or chemical markers do not seem to efficiently avert trade in illicit imitation products, RFID technology, with its potential to automate product authentications, may become a powerful tool to enhance brand and product protection. The following contribution contains an overview on the implication of product counterfeiting on affected companies, provides a starting point for a structured requirements definition for RFID-based anti-counterfeiting systems, and outlines several principal solution approaches that are discussed in greater detail in the subsequent chapters. © 2008 Springer-Verlag Berlin Heidelberg.

Functional genomic hypothesis generation and experimentation by a robot scientist

King R. D., Whelan, K. E., Jones, F. M., Reiser, P. G. K., Bryant, C. H., Muggleton, S., Kell, D. B. and Oliver, S. G. (2004) Functional genomic hypothesis generation and experimentation by a robot scientist. Nature 427 (6971) p247-252

Causality enabled compositional modelling of Bayesian networks

J. Keppens and Q. Shen. Causality enabled compositional modelling of Bayesian networks. Proceedings of the 18th International Workshop on Qualitative Reasoning, pages 33-40, 2004.

Intelligent Assembly Systems

Lee, M.H. and Rowland, J.J. (eds.), 1995, Intelligent Assembly Systems, 239pp, World Scientific series in Robotics and Intelligent Systems - Vol. 12, World Scientific, ISBN 981022494X.

Inspection of teats by colour image analysis for automatic milking systems

C.R. Bull, N.J.B. McFarlane, R. Zwiggelaar, C.J. Allen and T.T. Mottram, 'Inspection of teats by colour image analysis for automatic milking systems', Computers and Electronics in Agriculture 15 (1), 15-26 (1996)

Computer aided parallelisation tools (CAPTools) — conceptual overview and performance on the parallelisation of structured mesh codes

Computer Aided Parallelisation Tools (CAPTools) is a toolkit designed to automate as much as possible of the process of parallelising scalar FORTRAN 77 codes. The toolkit combines a very powerful dependence analysis together with user supplied knowledge to build an extremely comprehensive and accurate dependence graph. The initial version has been targeted at structured mesh computational mechanics codes (eg. heat transfer, Computational Fluid Dynamics (CFD)) and the associated simple mesh decomposition paradigm is utilised in the automatic code partition, execution control mask generation and communication call insertion. In this, the first of a series of papers [1–3] the authors discuss the parallelisations of a number of case study codes showing how the various component tools may be used to develop a highly efficient parallel implementation in a few hours or days. The details of the parallelisation of the TEAMKE1 CFD code are described together with the results of three other numerical codes. The resulting parallel implementations are then tested on workstation clusters using PVM and an i860-based parallel system showing efficiencies well over 80%.

The ParaWise expert assistant - widening accessibility to efficient and scalable tool Generated OpenMP code

Despite the apparent simplicity of the OpenMP directive shared memory programming model and the sophisticated dependence analysis and code generation capabilities of the ParaWise/CAPO tools, experience shows that a level of expertise is required to produce efficient parallel code. In a real world application the investigation of a single loop in a generated parallel code can soon become an in-depth inspection of numerous dependencies in many routines. The additional understanding of dependencies is also needed to effectively interpret the information provided and supply the required feedback. The ParaWise Expert Assistant has been developed to automate this investigation and present questions to the user about, and in the context of, their application code. In this paper, we demonstrate that knowledge of dependence information and OpenMP are no longer essential to produce efficient parallel code with the Expert Assistant. It is hoped that this will enable a far wider audience to use the tools and subsequently, exploit the benefits of large parallel systems.

A comparison between randomly alternating imaging, normal laparoscopic imaging, and virtual reality training in laparoscopic psychomotor skill acquisition

Objectives: To evaluate virtual reality as a laparoscopic training device in helping surgeons to automate to the “fulcrum effect” by comparing it to time-matched training programs using randomly alternating images (ie, y-axis inverted and normal laparoscopic) and normal laparoscopic viewing conditions.

Methods: Twenty-four participants (16 females and 8 males), were randomly assigned to minimally invasive surgery virtual reality (MIST VR), randomly alternating (between y-axis inverted and normal laparoscopic images), and normal laparoscopic imaging condition. Participants were requested to perform a 2-minute laparoscopic cutting task before and after training.

Results: In the test trial participants who trained on the MIST VR performed significantly better than those in the normal laparoscopic and randomly alternating imaging conditions.

Conclusion: The results show that virtual reality training may provide faster skill acquisition with particular reference to automation of the fulcrum effect. MIST VR provides a new way of training laparoscopic psychomotor surgical skills.

Adaptive automated construction of hybrid heuristics for exam timetabling and graph colouring problems

In this paper, we present a random iterative graph based hyper-heuristic to produce a collection of heuristic sequences to construct solutions of different quality. These heuristic sequences can be seen as dynamic hybridisations of different graph colouring heuristics that construct solutions step by step. Based on these sequences, we statistically analyse the way in which graph colouring heuristics are automatically hybridised. This, to our knowledge, represents a new direction in hyper-heuristic research. It is observed that spending the search effort on hybridising Largest Weighted Degree with Saturation Degree at the early stage of solution construction tends to generate high quality solutions. Based on these observations, an iterative hybrid approach is developed to adaptively hybridise these two graph colouring heuristics at different stages of solution construction. The overall aim here is to automate the heuristic design process, which draws upon an emerging research theme on developing computer methods to design and adapt heuristics automatically. Experimental results on benchmark exam timetabling and graph colouring problems demonstrate the effectiveness and generality of this adaptive hybrid approach compared with previous methods on automatically generating and adapting heuristics. Indeed, we also show that the approach is competitive with the state of the art human produced methods.

An Integration Methodology for Automated Recurring Cost Prediction using Digital Manufacturing Technology

The need to account for the effect of design decisions on manufacture and the impact of manufacturing cost on the life cycle cost of any product are well established. In this context, digital design and manufacturing solutions have to be further developed to facilitate and automate the integration of cost as one of the major driver in the product life cycle management. This article is to present an integration methodology for implementing cost estimation capability within a digital manufacturing environment. A digital manufacturing structure of knowledge databases are set out and the ontology of assembly and part costing that is consistent with the structure is provided. Although the methodology is currently used for recurring cost prediction, it can be well applied to other functional developments, such as process planning. A prototype tool is developed to integrate both assembly time cost and parts manufacturing costs within the same digital environment. An industrial example is used to validate this approach.