Paper
5 June 2014 Partially occluded object reconstruction using multiple Kinect sensors
Tabassum Nasrin, Faliu Yi, Samarjit Das, Inkyu Moon
Author Affiliations +
Abstract
In this paper, we propose a new method for the occluded object visualization using multiple Kinect sensors. The quality of occluded object reconstructed from conventional reconstruction method with elemental images captured by common camera arrays in integral imaging is usually degraded due to the existence of occlusion object in the 3D space which is a common case in reality. Even though some occlusion removal algorithms were proposed to improve the resolution of reconstructed occluded object, all of them are very time-consuming and make the 3D object reconstruction process inefficient. On the contrary, the Kinect sensors not only provide RGB images but also depth images. Since the depth and RGB color image is captured by two different cameras on Kinect sensor at different location, the depth image should be mapped to the color image. After image mapping (or registration), the same pixel location on depth and RGB color image would represent the same 3D space point. As result, the depth image after mapping can be used to remove the occlusion object in the corresponding RGB image (or elemental image) before doing object reconstruction in integral imaging. Consequently, the occluded object can be visualized with a high quality and will not take a long time as other methods.
© (2014) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Tabassum Nasrin, Faliu Yi, Samarjit Das, and Inkyu Moon "Partially occluded object reconstruction using multiple Kinect sensors", Proc. SPIE 9117, Three-Dimensional Imaging, Visualization, and Display 2014, 91171G (5 June 2014); https://doi.org/10.1117/12.2053938
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CITATIONS
Cited by 4 scholarly publications.
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KEYWORDS
3D image processing

Sensors

Integral imaging

RGB color model

Image registration

3D displays

3D image reconstruction

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