Zhu, Z and Ndiour, IJ and Brilakis, I and Vela, PA (2010) Improvements to Concrete Column Detection in Live Video. In: UNSPECIFIED pp. 108-117..Full text not available from this repository.
The automated detection of structural elements (e.g. concrete columns) in visual data is useful in many construction and maintenance applications. The research in this area is under initial investigation. The authors previously presented a concrete column detection method that utilized boundary and color information as detection cues. However, the method is sensitive to parameter selection, which reduces its ability to robustly detect concrete columns in live videos. Compared against the previous method, the new method presented in this paper reduces the reliance of parameter settings mainly in three aspects. First, edges are located using color information. Secondly, the orientation information of edge points is considered in constructing column boundaries. Thirdly, an artificial neural network for concrete material classification is developed to replace concrete sample matching. The method is tested using live videos, and results are compared with the results obtained with the previous method to demonstrate the new method improvements.
|Item Type:||Conference or Workshop Item (UNSPECIFIED)|
|Uncontrolled Keywords:||robust detection concrete columns live videos|
|Divisions:||Div D > Construction Engineering|
|Depositing User:||Unnamed user with email firstname.lastname@example.org|
|Date Deposited:||09 Dec 2016 18:40|
|Last Modified:||22 Jan 2017 00:50|