No abstract

No abstract

Accurate analyses of equipment idle time is crucial for the efficient utilization of construction equipment in a large construction project. The less idle time the equipment has, the higher productivity the construction can achieve. However, it is not practical to measure construction equipment idle time by human visual observation. This paper describes an image processing-based methodology to automatically quantify the idle time of construction equipment. The image color space, HSV (Hues, Saturations, and Values), is used as the basis for image segmentation and tracing algorithms. The HSV color space shows significant advantages over the RGB (Red, Green, and Blue) color space in identifying and tracing construction equipment. The centroid coordinates of equipment are used as the indicators of movement. Experimental results show that the proposed methodology has a promising potential for effective equipment management in construction projects.

Image database creation for infrastructure management is an interdisciplinary endeavor in computer vision, database, and structural engineering. In response to increasing demands for multimedia information in infrastructure management, image databases are becoming an ever more active research area. This paper proposes an automated system for creating an urban infrastructure 3D model using an image database; the system is built by images shot in public areas to record changes of urban infrastructure in threedimensional (3D) space, such as the addition of new buildings, new overpasses, loss of traffic signs, and growth/change of trees. The system architecture is presented with an emphasis on a 3D information capture and extraction module. Initial experiments with the 3D information capture module show that the proposed system has the potential to efficiently develop a large-scale 3D model of the streets of a municipality.