Characterizing Construction Equipment Activities in Long Video Sequences of Earthmoving Operations via Kinematic Features

Ruxiao Bao, Mohammad Amin Sadeghi, Mani Golparvar-Fard

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

Abstract

This paper presents a fast and scalable method for activity analysis of construction equipment involved in earthmoving operations from highly varying long-sequence videos obtained from fixed cameras. A common approach to characterize equipment activities consists of detecting and tracking the equipment within the video volume, recognizing interest points and describing them locally, and following by a bag-of-words representation for classifying activities. While successful results have been achieved in each aspect of detection, tracking, and activity recognition, the highly varying degree of intra-class variability in resources, occlusions and scene clutter, the difficulties in defining visually-distinct activities, together with long computational time have challenged scalability of current solutions. In this paper, we present a new end-to-end automated method to recognize the equipment activities by simultaneously detecting and tracking features, and characterizing the spatial kinematics of features via a decision tree. The method is tested on an unprecedented dataset of 5hr-long real-world videos of interacting pairs of excavators and trucks. The Experimental results show that the method is capable of activity recognition with accuracy of 88.91% with a computational time less than one-to-one ratio for each video length. The benefits of the proposed method for root-cause assessment of performance deviations are discussed.

Original languageEnglish (US)
Title of host publicationConstruction Research Congress 2016
Subtitle of host publicationOld and New Construction Technologies Converge in Historic San Juan - Proceedings of the 2016 Construction Research Congress, CRC 2016
EditorsJose L. Perdomo-Rivera, Carla Lopez del Puerto, Antonio Gonzalez-Quevedo, Francisco Maldonado-Fortunet, Omar I. Molina-Bas
PublisherAmerican Society of Civil Engineers
Pages849-858
Number of pages10
ISBN (Electronic)9780784479827
DOIs
StatePublished - 2016
EventConstruction Research Congress 2016: Old and New Construction Technologies Converge in Historic San Juan, CRC 2016 - San Juan, Puerto Rico
Duration: May 31 2016Jun 2 2016

Publication series

NameConstruction Research Congress 2016: Old and New Construction Technologies Converge in Historic San Juan - Proceedings of the 2016 Construction Research Congress, CRC 2016

Other

OtherConstruction Research Congress 2016: Old and New Construction Technologies Converge in Historic San Juan, CRC 2016
CountryPuerto Rico
CitySan Juan
Period5/31/166/2/16

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Building and Construction

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