Comparison of manual and user guided methodologies for the classification and retrieval of construction site images

The amount of original imaging information produced yearly during the last decade has experienced a tremendous growth in all industries due to the technological breakthroughs in digital imaging and electronic storage capabilities. This trend is affecting the construction industry as well, where digital cameras and image databases are gradually replacing traditional photography. Owners demand complete site photograph logs and engineers store thousands of images for each project to use in a number of construction management tasks like monitoring an activity's progress and keeping evidence of the "as built" in case any disputes arise. So far, retrieval methodologies are done manually with the user being responsible for imaging classification according to specific rules that serve a limited number of construction management tasks. New methods that, with the guidance of the user, can automatically classify and retrieve construction site images are being developed and promise to remove the heavy burden of manually indexing images. In this paper, both the existing methods and a novel image retrieval method developed by the authors for the classification and retrieval of construction site images are described and compared. Specifically a number of examples are deployed in order to present their advantages and limitations. The results from this comparison demonstrates that the content based image retrieval method developed by the authors can reduce the overall time spent for the classification and retrieval of construction images while providing the user with the flexibility to retrieve images according different classification schemes.

Validation of Vision Tracking at Egnatia Odos Motorway

Tracking applications provide real time on-site information that can be used to detect travel path conflicts, calculate crew productivity and eliminate unnecessary processes at the site. This paper presents the validation of a novel vision based tracking methodology at the Egnatia Odos Motorway in Thessaloniki, Greece. Egnatia Odos is a motorway that connects Turkey with Italy through Greece. Its multiple open construction sites serves as an ideal multi-site test bed for validating construction site tracking methods. The vision based tracking methodology uses video cameras and computer algorithms to calculate the 3D position of project related entities (e.g. personnel, materials and equipment) in construction sites. The approach provides an unobtrusive, inexpensive way of effectively identifying and tracking the 3D location of entities. The process followed in this study starts by acquiring video data from multiple synchronous cameras at several large scale project sites of Egnatia Odos, such as tunnels, interchanges and bridges under construction. Subsequent steps include the evaluation of the collected data and finally, performing the 3D tracking operations on selected entities (heavy equipment and personnel). The accuracy and precision of the method's results is evaluated by comparing it with the actual 3D position of the object, thus assessing the 3D tracking method's effectiveness.

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.

Comparison of Image-Based and Time-of-Flight-Based Technologies for 3D Reconstruction of Infrastructure

Image-based (i.e., photo/videogrammetry) and time-of-flight-based (i.e., laser scanning) technologies are typically used to collect spatial data of infrastructure. In order to help architecture, engineering, and construction (AEC) industries make cost-effective decisions in selecting between these two technologies with respect to their settings, this paper makes an attempt to measure the accuracy, quality, time efficiency, and cost of applying image-based and time-of-flight-based technologies to conduct as-built 3D reconstruction of infrastructure. In this paper, a novel comparison method is proposed, and preliminary experiments are conducted. The results reveal that if the accuracy and quality level desired for a particular application is not high (i.e., error < 10 cm, and completeness rate > 80%), image-based technologies constitute a good alternative for time-of-flight-based technologies and significantly reduce the time and cost needed for collecting the data on site.

Modelling and Fragility Analysis of Non-Ductile Reinforced Concrete Buildings in Low-to-Moderate Seismic Zones

Reinforced concrete buildings in low-to-moderate seismic zones are often designed only for gravity loads in accordance with the non-seismic detailing provisions. Deficient detailing of columns and beam-column joints can lead to unpredictable brittle failures even under moderate earthquakes. Therefore, a reliable estimate of structural response is required for the seismic evaluation of these structures. For this purpose, analytical models for both interior and exterior slab-beam-column subassemblages and for a 1/3 scale model frame were implemented into the nonlinear finite element platform OpenSees. Comparison between the analytical results and experimental data available in the literature is carried out using nonlinear pushover analyses and nonlinear time history analysis for the subassemblages and the model frame, respectively. Furthermore, the seismic fragility assessment of reinforced concrete buildings is performed on a set of non-ductile frames using nonlinear time history analyses. The fragility curves, which are developed for various damage states for the maximum interstory drift ratio are characterized in terms of peak ground acceleration and spectral acceleration using a suite of ground motions representative of the seismic hazard in the region.

Population of nonnative states of lysozyme variants drives amyloid fibril formation.

The propensity of protein molecules to self-assemble into highly ordered, fibrillar aggregates lies at the heart of understanding many disorders ranging from Alzheimer's disease to systemic lysozyme amyloidosis. In this paper we use highly accurate kinetic measurements of amyloid fibril growth in combination with spectroscopic tools to quantify the effect of modifications in solution conditions and in the amino acid sequence of human lysozyme on its propensity to form amyloid fibrils under acidic conditions. We elucidate and quantify the correlation between the rate of amyloid growth and the population of nonnative states, and we show that changes in amyloidogenicity are almost entirely due to alterations in the stability of the native state, while other regions of the global free-energy surface remain largely unmodified. These results provide insight into the complex dynamics of a macromolecule on a multidimensional energy landscape and point the way for a better understanding of amyloid diseases.