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3D Scene Sensing and Object Recording
Volume: 28 | Article ID: art00015
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Shadow Detection on 3D Point Cloud
  DOI :  10.2352/ISSN.2470-1173.2016.21.3DIPM-044  Published OnlineFebruary 2016
Abstract

Shadow detection is undergoing active research because it plays an important role in scene understanding, and has a wide range of applications including household robots and autonomous cars. In this effort, we present a novel approach to detect cast shadows on 3D point clouds. Point Cloud Library (PCL) is used to perform plane detection on point clouds. A Markov Random Field (MRF) is then constructed on the detected plane region, with an energy term that combines plane labels, depth cues and brightness cues. The resulting system is tested against USC Shadow, a dataset we collected in a controlled environment, as well as selected scenes from NYU Depth, a dataset that contains 1449 RGB-D images of various indoor scenes. Our system shows very stable performance even on complicated scenes and heavily textured planes.

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  Cite this article 

Shuyang Sheng, B. Keith Jenkins, "Shadow Detection on 3D Point Cloudin Proc. IS&T Int’l. Symp. on Electronic Imaging: 3D Image Processing, Measurement (3DIPM), and Applications,  2016,  https://doi.org/10.2352/ISSN.2470-1173.2016.21.3DIPM-044

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Copyright © Society for Imaging Science and Technology 2016
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Electronic Imaging
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