Video-based highway asset recognition and 3D localization

Vahid Balali, Mani Golparvar-Fard, Jesus M. De La Garza

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

A key element towards development of an asset management program is an efficient data collection on high-quantity, low-cost highway assets. Despite the importance, current practices of asset data collection are still manual and time-consuming. There is a need for a well-managed asset data collection that can provide usable asset inventories to Departments of Transportation (DOTs) for further analysis and condition assessment purposes. In this paper, we present a novel video-based recognition and 3D reconstruction algorithm. Our method takes an input of video streams and combines 2D recognition with 3D reconstruction algorithms. Using a new Support Vector Machine (SVM) classifier and based on the color channels at pixel level, a set of bounding boxes is initially extracted. Using a Haar-based shape recognition algorithm, the 2D candidates are further categorized based on their shape. These candidates are placed into a texture? recognition algorithm. The benefits and limitations of the method in detection, classification, and localization of multiple types of assets are discussed in detail.

Original languageEnglish (US)
Title of host publicationComputing in Civil Engineering - Proceedings of the 2013 ASCE International Workshop on Computing in Civil Engineering
PublisherAmerican Society of Civil Engineers
Pages379-386
Number of pages8
ISBN (Print)9780784477908
DOIs
StatePublished - Jan 1 2013
Event2013 ASCE International Workshop on Computing in Civil Engineering, IWCCE 2013 - Los Angeles, CA, United States
Duration: Jun 23 2013Jun 25 2013

Publication series

NameComputing in Civil Engineering - Proceedings of the 2013 ASCE International Workshop on Computing in Civil Engineering

Other

Other2013 ASCE International Workshop on Computing in Civil Engineering, IWCCE 2013
CountryUnited States
CityLos Angeles, CA
Period6/23/136/25/13

ASJC Scopus subject areas

  • Civil and Structural Engineering

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  • Cite this

    Balali, V., Golparvar-Fard, M., & De La Garza, J. M. (2013). Video-based highway asset recognition and 3D localization. In Computing in Civil Engineering - Proceedings of the 2013 ASCE International Workshop on Computing in Civil Engineering (pp. 379-386). (Computing in Civil Engineering - Proceedings of the 2013 ASCE International Workshop on Computing in Civil Engineering). American Society of Civil Engineers. https://doi.org/10.1061/9780784413029.048