A Cross-Based Spatio-Temporal Local Stereo Matching
碩士 === 國立成功大學 === 電腦與通信工程研究所 === 102 === Traditional stereo matching algorithm estimates disparity by using spatial information in one pair of images, but it is easy to estimate error and generate noise due to repeated textures or occlusion. When we calculate the disparity for sequential images,...
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ndltd-TW-102NCKU56520012016-07-02T04:20:39Z http://ndltd.ncl.edu.tw/handle/08113817449718573432 A Cross-Based Spatio-Temporal Local Stereo Matching 基於十字的時空區域性立體匹配演算法 Pang-WeiWang 王邦威 碩士 國立成功大學 電腦與通信工程研究所 102 Traditional stereo matching algorithm estimates disparity by using spatial information in one pair of images, but it is easy to estimate error and generate noise due to repeated textures or occlusion. When we calculate the disparity for sequential images, the noise situation in each frame may be different due to the movement of objects, and flickering-artifacts will be produced when you play the depth map. In this paper, we propose a cross-based spatio-temporal local stereo matching. By adding temporal information when we estimate disparity, we hope to achieve depth consistency. In the beginning, we construct a support region for each pixel, then we find the similarities in their colors, surrounding textures and the shape of support regions of two pixels. Next, when we estimate the disparity of each pixel, we track the location of each pixel in the preceding frame and reference their information, and we use the penalty restriction to make the disparity computed by two frames consistent. In the end, we perform post-processing methods, such as left-right consistency check and temporal consistency of depth sequence to repair and smooth the spatial and temporal depth. The experimental results show that our method can effectively avoid the errors caused by repeated textures, while reducing the flickering-artifacts and maintaining the depth boundary of the object. Pau-Choo Chung 詹寶珠 2014 學位論文 ; thesis 44 zh-TW |
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碩士 === 國立成功大學 === 電腦與通信工程研究所 === 102 === Traditional stereo matching algorithm estimates disparity by using spatial information in one pair of images, but it is easy to estimate error and generate noise due to repeated textures or occlusion. When we calculate the disparity for sequential images, the noise situation in each frame may be different due to the movement of objects, and flickering-artifacts will be produced when you play the depth map. In this paper, we propose a cross-based spatio-temporal local stereo matching. By adding temporal information when we estimate disparity, we hope to achieve depth consistency. In the beginning, we construct a support region for each pixel, then we find the similarities in their colors, surrounding textures and the shape of support regions of two pixels. Next, when we estimate the disparity of each pixel, we track the location of each pixel in the preceding frame and reference their information, and we use the penalty restriction to make the disparity computed by two frames consistent. In the end, we perform post-processing methods, such as left-right consistency check and temporal consistency of depth sequence to repair and smooth the spatial and temporal depth. The experimental results show that our method can effectively avoid the errors caused by repeated textures, while reducing the flickering-artifacts and maintaining the depth boundary of the object.
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Pau-Choo Chung |
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Pau-Choo Chung Pang-WeiWang 王邦威 |
author |
Pang-WeiWang 王邦威 |
spellingShingle |
Pang-WeiWang 王邦威 A Cross-Based Spatio-Temporal Local Stereo Matching |
author_sort |
Pang-WeiWang |
title |
A Cross-Based Spatio-Temporal Local Stereo Matching |
title_short |
A Cross-Based Spatio-Temporal Local Stereo Matching |
title_full |
A Cross-Based Spatio-Temporal Local Stereo Matching |
title_fullStr |
A Cross-Based Spatio-Temporal Local Stereo Matching |
title_full_unstemmed |
A Cross-Based Spatio-Temporal Local Stereo Matching |
title_sort |
cross-based spatio-temporal local stereo matching |
publishDate |
2014 |
url |
http://ndltd.ncl.edu.tw/handle/08113817449718573432 |
work_keys_str_mv |
AT pangweiwang acrossbasedspatiotemporallocalstereomatching AT wángbāngwēi acrossbasedspatiotemporallocalstereomatching AT pangweiwang jīyúshízìdeshíkōngqūyùxìnglìtǐpǐpèiyǎnsuànfǎ AT wángbāngwēi jīyúshízìdeshíkōngqūyùxìnglìtǐpǐpèiyǎnsuànfǎ AT pangweiwang crossbasedspatiotemporallocalstereomatching AT wángbāngwēi crossbasedspatiotemporallocalstereomatching |
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