Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B3, 663-667, 2016
http://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLI-B3/663/2016/
doi:10.5194/isprs-archives-XLI-B3-663-2016
 
10 Jun 2016
APPLICATION FOR 3D SCENE UNDERSTANDING IN DETECTING DISCHARGE OF DOMESTICWASTE ALONG COMPLEX URBAN RIVERS
Y. Ninsalam1,3, R. Qin2, and J. Rekittke1 1National University of Singapore, Department of Architecture, 4 Architecture Drive Singapore 117566
2The Ohio State University, Department of Civil, Environmental Engineering and Geodetic Engineering, 470 Hitchcock Hall 2070 Neil Avenue, Columbus, OH 43210, USA
3Singapore-ETH Centre, Future Cities Laboratory, CREATE Tower Singapore 138602
Keywords: Scene Understanding, Image Classification, Co-Registration, Urban Rivers, Complex Terrain 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.
Conference paper (PDF, 8068 KB)


Citation: Ninsalam, Y., Qin, R., and Rekittke, J.: APPLICATION FOR 3D SCENE UNDERSTANDING IN DETECTING DISCHARGE OF DOMESTICWASTE ALONG COMPLEX URBAN RIVERS, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B3, 663-667, doi:10.5194/isprs-archives-XLI-B3-663-2016, 2016.

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