IREE: Automated Vision Tracking of Project Related Entities

The purpose of this supplemental project was to collect invaluable data from the large-scale construction sites of Egnatia Odos motorway needed to validate a novel automated vision-tracking method created under the parent grant. For this purpose, one US graduate and three US undergraduate students traveled to Greece for 4 months and worked together with 2 Greek graduate students of the local faculty collaborator. This team of students monitored project activities and scheduled data collection trips on a daily basis, setup a mobile video data collection lab on the back of a truck, and drove to various sites every day to collect hundreds of hours of video from multiple cameras on a large variety of activities ranging from soil excavation to bridge construction. The US students were underrepresented students from minority groups who had never visited a foreign country. As a result, this trip was a major life experience to them. They learned how to live in a non-English speaking country, communicate with Greek students, workers and engineers. They lead a project in a very unfamiliar environment, troubleshoot myriad problems that hampered their progress daily and, above all, how to collaborate effectively and efficiently with other cultures. They returned to the US more mature, with improved leadership and problem-solving skills and a wider perspective of their profession.

Construction Worker Detection in Video Frames for Initializing Vision Trackers

Monitoring the location of resources on large scale, congested, outdoor sites can be performed more efficiently with vision tracking, as this approach does not require any pre-tagging of resources. However, the greatest impediment to the use of vision tracking in this case is the lack of detection methods that are needed to automatically mark the resources of interest and initiate the tracking. This paper presents such a novel method for construction worker detection that localizes construction workers in video frames. The proposed method exploits motion, shape, and color cues to narrow down the detection regions to moving objects, people, and finally construction workers, respectively. The three cues are characterized by using background subtraction, the histogram of oriented gradients (HOG), and the HSV color histogram. The method has been tested on videos taken in various environments. The results demonstrate its suitability for automatic initialization of vision trackers.

Innovative Stereo Vision-Based Approach to Generate Dense Depth Map of Transportation Infrastructure

Three-dimensional (3-D) spatial data of a transportation infrastructure contain useful information for civil engineering applications, including as-built documentation, on-site safety enhancements, and progress monitoring. Several techniques have been developed for acquiring 3-D point coordinates of infrastructure, such as laser scanning. Although the method yields accurate results, the high device costs and human effort required render the process infeasible for generic applications in the construction industry. A quick and reliable approach, which is based on the principles of stereo vision, is proposed for generating a depth map of an infrastructure. Initially, two images are captured by two similar stereo cameras at the scene of the infrastructure. A Harris feature detector is used to extract feature points from the first view, and an innovative adaptive window-matching technique is used to compute feature point correspondences in the second view. A robust algorithm computes the nonfeature point correspondences. Thus, the correspondences of all the points in the scene are obtained. After all correspondences have been obtained, the geometric principles of stereo vision are used to generate a dense depth map of the scene. The proposed algorithm has been tested on several data sets, and results illustrate its potential for stereo correspondence and depth map generation.

Data Analysis on Complicated Construction Data Sources: Vision, Research, and Recent Developments

Compared with construction data sources that are usually stored and analyzed in spreadsheets and single data tables, data sources with more complicated structures, such as text documents, site images, web pages, and project schedules have been less intensively studied due to additional challenges in data preparation, representation, and analysis. In this paper, our definition and vision for advanced data analysis addressing such challenges are presented, together with related research results from previous work, as well as our recent developments of data analysis on text-based, image-based, web-based, and network-based construction sources. It is shown in this paper that particular data preparation, representation, and analysis operations should be identified, and integrated with careful problem investigations and scientific validation measures in order to provide general frameworks in support of information search and knowledge discovery from such information-abundant data sources.

Comprehensive Property Retrieval and Measurement of Concrete Spalling Using Machine Vision for Post-Earthquake Safety Assessments

Active vibration control (AVC) is a relatively new technology for the mitigation of annoying human-induced vibrations in floors. However, recent technological developments have demonstrated its great potential application in this field. Despite this, when a floor is found to have problematic floor vibrations after construction the unfamiliar technology of AVC is usually avoided in favour of more common techniques, such as Tuned Mass Dampers (TMDs) which have a proven track record of successful application, particularly for footbridges and staircases. This study aims to investigate the advantages and disadvantages that AVC has, when compared with TMDs, for the application of mitigation of pedestrian-induced floor vibrations in offices. Simulations are performed using the results from a finite element model of a typical office layout that has a high vibration response level. The vibration problems on this floor are then alleviated through the use of both AVC and TMDs and the results of each mitigation configuration compared. The results of this study will enable a more informed decision to be made by building owners and structural engineers regarding suitable technologies for reducing floor vibrations.

Calculation of point defects in rutile TiO 2 by the screened-exchange hybrid functional

The formation energies of the oxygen vacancy and titanium interstitial in rutile TiO 2 were calculated by the screened-exchange (sX) hybrid density functional method, which gives a band gap of 3.1 eV, close to the experimental value. The oxygen vacancy gives rise to a gap state lying 0.7 eV below the conduction band edge, whose charge density is localized around the two of three Ti atoms next to the vacancy. The Ti interstitial (Ti int) generates four defect states in the gap, whose unpaired electrons lie on the interstitial and the adjacent Ti 3d orbitals. The formation energy for the neutral oxygen vacancy is 1.9 eV for the O-poor chemical potential. The neutral Ti interstitial has a lower formation energy than the O vacancy under O-poor conditions. This indicates that both the O vacancy and Ti int are relevant for oxygen deficiency in rutile TiO 2 but the O vacancy will dominate under O-rich conditions. This resolves questions about defect localization and defect predominance in the literature. © 2012 American Physical Society.

Rapid entropy-based detection and properties measurement of concrete spalling with machine vision for post-earthquake safety assessments

The current procedures in post-earthquake safety and structural assessment are performed manually by a skilled triage team of structural engineers/certified inspectors. These procedures, and particularly the physical measurement of the damage properties, are time-consuming and qualitative in nature. This paper proposes a novel method that automatically detects spalled regions on the surface of reinforced concrete columns and measures their properties in image data. Spalling has been accepted as an important indicator of significant damage to structural elements during an earthquake. According to this method, the region of spalling is first isolated by way of a local entropy-based thresholding algorithm. Following this, the exposure of longitudinal reinforcement (depth of spalling into the column) and length of spalling along the column are measured using a novel global adaptive thresholding algorithm in conjunction with image processing methods in template matching and morphological operations. The method was tested on a database of damaged RC column images collected after the 2010 Haiti earthquake, and comparison of the results with manual measurements indicate the validity of the method.

Functional requirements for reward-modulated spike-timing-dependent plasticity.

Recent experiments have shown that spike-timing-dependent plasticity is influenced by neuromodulation. We derive theoretical conditions for successful learning of reward-related behavior for a large class of learning rules where Hebbian synaptic plasticity is conditioned on a global modulatory factor signaling reward. We show that all learning rules in this class can be separated into a term that captures the covariance of neuronal firing and reward and a second term that presents the influence of unsupervised learning. The unsupervised term, which is, in general, detrimental for reward-based learning, can be suppressed if the neuromodulatory signal encodes the difference between the reward and the expected reward-but only if the expected reward is calculated for each task and stimulus separately. If several tasks are to be learned simultaneously, the nervous system needs an internal critic that is able to predict the expected reward for arbitrary stimuli. We show that, with a critic, reward-modulated spike-timing-dependent plasticity is capable of learning motor trajectories with a temporal resolution of tens of milliseconds. The relation to temporal difference learning, the relevance of block-based learning paradigms, and the limitations of learning with a critic are discussed.