|
|
|
|
| LEADER |
01000naa a22002652 4500 |
| 001 |
NLM180459163 |
| 003 |
DE-627 |
| 005 |
20231223155523.0 |
| 007 |
cr uuu---uuuuu |
| 008 |
231223s2004 xx |||||o 00| ||eng c |
| 024 |
7 |
|
|a 10.1109/TPAMI.2004.10
|2 doi
|
| 028 |
5 |
2 |
|a pubmed24n0602.xml
|
| 035 |
|
|
|a (DE-627)NLM180459163
|
| 035 |
|
|
|a (NLM)18579937
|
| 040 |
|
|
|a DE-627
|b ger
|c DE-627
|e rakwb
|
| 041 |
|
|
|a eng
|
| 100 |
1 |
|
|a Jia, Jiaya
|e verfasserin
|4 aut
|
| 245 |
1 |
0 |
|a Inference of segmented color and texture description by tensor voting
|
| 264 |
|
1 |
|c 2004
|
| 336 |
|
|
|a Text
|b txt
|2 rdacontent
|
| 337 |
|
|
|a ƒaComputermedien
|b c
|2 rdamedia
|
| 338 |
|
|
|a ƒa Online-Ressource
|b cr
|2 rdacarrier
|
| 500 |
|
|
|a Date Completed 31.07.2008
|
| 500 |
|
|
|a Date Revised 26.06.2008
|
| 500 |
|
|
|a published: Print
|
| 500 |
|
|
|a Citation Status MEDLINE
|
| 520 |
|
|
|a A robust synthesis method is proposed to automatically infer missing color and texture information from a damaged 2D image by (N)D tensor voting (N > 3). The same approach is generalized to range and 3D data in the presence of occlusion, missing data and noise. Our method translates texture information into an adaptive (N)D tensor, followed by a voting process that infers noniteratively the optimal color values in the (N)D texture space. A two-step method is proposed. First, we perform segmentation based on insufficient geometry, color, and texture information in the input, and extrapolate partitioning boundaries by either 2D or 3D tensor voting to generate a complete segmentation for the input. Missing colors are synthesized using (N)D tensor voting in each segment. Different feature scales in the input are automatically adapted by our tensor scale analysis. Results on a variety of difficult inputs demonstrate the effectiveness of our tensor voting approach
|
| 650 |
|
4 |
|a Journal Article
|
| 650 |
|
4 |
|a Research Support, Non-U.S. Gov't
|
| 700 |
1 |
|
|a Tang, Chi-Keung
|e verfasserin
|4 aut
|
| 773 |
0 |
8 |
|i Enthalten in
|t IEEE transactions on pattern analysis and machine intelligence
|d 1979
|g 26(2004), 6 vom: 26. Juni, Seite 771-86
|w (DE-627)NLM098212257
|x 1939-3539
|7 nnns
|
| 773 |
1 |
8 |
|g volume:26
|g year:2004
|g number:6
|g day:26
|g month:06
|g pages:771-86
|
| 856 |
4 |
0 |
|u http://dx.doi.org/10.1109/TPAMI.2004.10
|3 Volltext
|
| 912 |
|
|
|a GBV_USEFLAG_A
|
| 912 |
|
|
|a SYSFLAG_A
|
| 912 |
|
|
|a GBV_NLM
|
| 912 |
|
|
|a GBV_ILN_350
|
| 951 |
|
|
|a AR
|
| 952 |
|
|
|d 26
|j 2004
|e 6
|b 26
|c 06
|h 771-86
|