Visual complexity analysis of sparse imageries for automatic laser scan planning in dynamic environments

Cheng Zhang, Pingbo Tang

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

3 Scopus citations

Abstract

Laser scanning technologies have significantly improved the efficiency of spatial data collection to deliver the needed as-built information of job sites. However, many imageries contain unneeded dense data that waste time for data collection and processing, or missing data that are in need. Targeted laser scan data collection is pivotal to avoid such problems. For example, engineers could avoid densely sampling simple geometries (e.g. flat walls) for saving time to focus on edges and openings. Scan planning algorithms can produce data collection plans based on targeted objects marked by users. Unfortunately, manually defining objects and their needed level of detail (LOD) is impractical in dynamic environments, such as construction sites. This research proposes an approach that identifies visually complex regions through discontinuity analysis in rapidly captured sparse imageries for guiding the imaging planning. First, we fuse 3D point cloud data with sparse laser-scan data. A visual complexity analysis algorithm then detects locations in sparse imageries that contain discontinuous 2D and 3D patterns (e.g., color change) for identifying parts deserving detailed laser scan. A frequency analysis for each location would then estimate the LOD necessary for assessing each targeted region. Finally, a sensor-planning algorithm generates laser scan plans based on visually complex regions and LOD requirements.

Original languageEnglish (US)
Title of host publicationComputing in Civil Engineering 2015 - Proceedings of the 2015 International Workshop on Computing in Civil Engineering
EditorsWilliam J. O'Brien, Simone Ponticelli
PublisherAmerican Society of Civil Engineers (ASCE)
Pages271-279
Number of pages9
EditionJanuary
ISBN (Electronic)9780784479247
DOIs
StatePublished - Jan 1 2015
Event2015 ASCE International Workshop on Computing in Civil Engineering, IWCCE 2015 - Austin, United States
Duration: Jun 21 2015Jun 23 2015

Publication series

NameCongress on Computing in Civil Engineering, Proceedings
NumberJanuary
Volume2015-January

Other

Other2015 ASCE International Workshop on Computing in Civil Engineering, IWCCE 2015
CountryUnited States
CityAustin
Period6/21/156/23/15

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Computer Science Applications

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    Zhang, C., & Tang, P. (2015). Visual complexity analysis of sparse imageries for automatic laser scan planning in dynamic environments. In W. J. O'Brien, & S. Ponticelli (Eds.), Computing in Civil Engineering 2015 - Proceedings of the 2015 International Workshop on Computing in Civil Engineering (January ed., pp. 271-279). (Congress on Computing in Civil Engineering, Proceedings; Vol. 2015-January, No. January). American Society of Civil Engineers (ASCE). https://doi.org/10.1061/9780784479247.034