Application for 3D scene understanding in detecting discharge of domestic waste along complex urban rivers

bin Ninsalam, M, Qin, R and Rekittke, J 2016, 'Application for 3D scene understanding in detecting discharge of domestic waste along complex urban rivers', International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives, vol. 41, pp. 663-667.


Document type: Journal Article
Collection: Journal Articles

Title Application for 3D scene understanding in detecting discharge of domestic waste along complex urban rivers
Author(s) bin Ninsalam, M
Qin, R
Rekittke, J
Year 2016
Journal name International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives
Volume number 41
Start page 663
End page 667
Total pages 5
Publisher Copernicus
Abstract In our study we use 3D scene understanding to detect the discharge of domestic solid waste along an urban river. Solid waste found along the Ciliwung River in the neighbourhoods of Bukit Duri and Kampung Melayu may be attributed to households. This is in part due to inadequate municipal waste infrastructure and services which has caused those living along the river to rely upon it for waste disposal. However, there has been little research to understand the prevalence of household waste along the river. Our aim is to develop a methodology that deploys a low cost sensor to identify point source discharge of solid waste using image classification methods. To demonstrate this we describe the following five-step method: 1) a strip of GoPro images are captured photogrammetrically and processed for dense point cloud generation; 2) depth for each image is generated through a backward projection of the point clouds; 3) a supervised image classification method based on Random Forest classifier is applied on the view dependent red, green, blue and depth (RGB-D) data; 4) point discharge locations of solid waste can then be mapped by projecting the classified images to the 3D point clouds; 5) then the landscape elements are classified into five types, such as vegetation, human settlement, soil, water and solid waste. While this work is still ongoing, the initial results have demonstrated that it is possible to perform quantitative studies that may help reveal and estimate the amount of waste present along the river bank.
Subject Photogrammetry and Remote Sensing
Keyword(s) Co-Registration
Complex Terrain
Image Classification
Scene Understanding
Urban Rivers
DOI - identifier 10.5194/isprsarchives-XLI-B3-663-2016
ISSN 1682-1750
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