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http://hdl.handle.net/11375/18790
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DC Field | Value | Language |
---|---|---|
dc.contributor.advisor | Wu, Xiaolin | - |
dc.contributor.author | Deng, Xiaowei | - |
dc.date.accessioned | 2016-02-02T19:25:15Z | - |
dc.date.available | 2016-02-02T19:25:15Z | - |
dc.date.issued | 2016 | - |
dc.identifier.uri | http://hdl.handle.net/11375/18790 | - |
dc.description.abstract | Many tasks of visual computing and communications such as object recognition, matting, compression, etc., need to extract and encode the outer boundary of the object in a digital image or video. In this thesis, we focus on a particular video segmentation task and propose an efficient method for head-and-shoulder of humans through video frames. The key innovations for our work are as follows: (1) a novel head descriptor in polar coordinate is proposed, which can characterize intrinsic head object well and make it easy for computer to process, classify and recognize. (2) a learning-based method is proposed to provide highly precise and robust head-and-shoulder segmentation results in applications where the head-and-shoulder object in the question is a known prior and the background is too complex. The efficacy of our method is demonstrated on a number of challenging experiments. | en_US |
dc.language.iso | en | en_US |
dc.subject | head-and-shoulder | en_US |
dc.subject | segmentation | en_US |
dc.subject | learning-based | en_US |
dc.subject | dynamic programming | en_US |
dc.title | Fast Head-and-shoulder Segmentation | en_US |
dc.type | Thesis | en_US |
dc.contributor.department | Electrical and Computer Engineering | en_US |
dc.description.degreetype | Thesis | en_US |
dc.description.degree | Master of Applied Science (MASc) | en_US |
Appears in Collections: | Open Access Dissertations and Theses |
Files in This Item:
File | Description | Size | Format | |
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thesis.pdf | Main article | 9.97 MB | Adobe PDF | View/Open |
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