Parallel Hierarchical 3-D Matching of RGB-D Images
碩士 === 國立暨南國際大學 === 資訊工程學系 === 101 === This thesis proposes a new method for RGB-D image matching which is different from the traditional point-to-point/point-to-plane matching methods. An objective function is proposed that fuses both depth and color information for estimating the transformation ma...
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| Other Authors: | |
| Format: | Others |
| Language: | zh-TW |
| Published: |
2013
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| Online Access: | http://ndltd.ncl.edu.tw/handle/cbae6h |
| Summary: | 碩士 === 國立暨南國際大學 === 資訊工程學系 === 101 === This thesis proposes a new method for RGB-D image matching which is different from
the traditional point-to-point/point-to-plane matching methods. An objective function is proposed
that fuses both depth and color information for estimating the transformation matrix
between two RGB-D images. A hierarchical scale space parameter estimation method is proposed
for dealing with image matching with large motion. The main idea is to smooth the
input image appropriately so that the minute features are temporarily ignored to simplify the
matching problem of main 3-D structures. Notably, image smoothing will eliminate a portion
of the image information. To fully utilize the RGB-D information, the degree of blurriness
is reduced gradually to introduce the minute image features into the parameter estimation
process in a coarse-to-fine matching approach. The image matching method is implemented
with CUDA parallel processing framework. Experimental results show that the proposed
method can efficiently match two RGB-D images.
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