Knowledge Commons of Institute of Automation,CAS
Depth map upsampling using compressive sensing based model | |
Dai, Longquan; Wang, Haoxing; Zhang, Xiaopeng | |
发表期刊 | NEUROCOMPUTING |
2015-04-22 | |
卷号 | 154页码:325-336 |
文章类型 | Article |
摘要 | We propose a new method to enhance the lateral resolution of depth maps with registered high-resolution color images. Inspired by the theory of compressive sensing (CS), we formulate the upsampling task as a sparse signal recovery problem that solves an underdetermined system. With a reference color image, the low-resolution depth map is converted into suitable sampling data (measurements). The signal recovery problem, defined in a constrained optimization framework, can be efficiently solved by variable splitting and alternating minimization. Experimental results demonstrate the effectiveness of our CS-based method: it competes favorably with other state-of-the-art methods with large upsampling factors and noisy depth inputs. (C) 2014 Elsevier B.V. All rights reserved. |
关键词 | Depth Map Compressive Sensing Upsampling |
WOS标题词 | Science & Technology ; Technology |
关键词[WOS] | UNCERTAINTY PRINCIPLES ; SIGNAL RECONSTRUCTION ; ATOMIC DECOMPOSITION ; OBJECT RECOGNITION ; PROJECTION |
收录类别 | SCI |
语种 | 英语 |
WOS研究方向 | Computer Science |
WOS类目 | Computer Science, Artificial Intelligence |
WOS记录号 | WOS:000350081900033 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/8083 |
专题 | 多模态人工智能系统全国重点实验室_多媒体计算 |
作者单位 | Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing, Peoples R China |
第一作者单位 | 模式识别国家重点实验室 |
推荐引用方式 GB/T 7714 | Dai, Longquan,Wang, Haoxing,Zhang, Xiaopeng. Depth map upsampling using compressive sensing based model[J]. NEUROCOMPUTING,2015,154:325-336. |
APA | Dai, Longquan,Wang, Haoxing,&Zhang, Xiaopeng.(2015).Depth map upsampling using compressive sensing based model.NEUROCOMPUTING,154,325-336. |
MLA | Dai, Longquan,et al."Depth map upsampling using compressive sensing based model".NEUROCOMPUTING 154(2015):325-336. |
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