Abstract
This paper proposes a novel method for estimating disparity accurately. To achieve the ideal result, an optimal adjusting framework is proposed to address the noise, occlusions, and outliners. Different from the typical multi-view stereo (MVS) methods, the proposed approach not only use the color constraint, but also use the geometric constraint associating multiple frame from the image sequence. The result shows the disparity with a good visual quality that most of the noise is eliminated, the errors in occlusion area are suppressed and the details of scene objects are preserved.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of SPIE - The International Society for Optical Engineering |
| Publisher | SPIE |
| Volume | 9445 |
| ISBN (Print) | 9781628415605 |
| DOIs | |
| Publication status | Published - 2015 |
| Event | 7th International Conference on Machine Vision, ICMV 2014 - Milan Duration: 2014 Nov 19 → 2014 Nov 21 |
Other
| Other | 7th International Conference on Machine Vision, ICMV 2014 |
|---|---|
| City | Milan |
| Period | 14/11/19 → 14/11/21 |
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Keywords
- Color constraint
- Disparity estimation
- Geometry constraint
- Multi-view stereo (MVS)
ASJC Scopus subject areas
- Applied Mathematics
- Computer Science Applications
- Electrical and Electronic Engineering
- Electronic, Optical and Magnetic Materials
- Condensed Matter Physics
Cite this
Disparity estimation from monocular image sequence. / Zhang, Qieshi; Kamata, Seiichiro.
Proceedings of SPIE - The International Society for Optical Engineering. Vol. 9445 SPIE, 2015. 944515.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Disparity estimation from monocular image sequence
AU - Zhang, Qieshi
AU - Kamata, Seiichiro
PY - 2015
Y1 - 2015
N2 - This paper proposes a novel method for estimating disparity accurately. To achieve the ideal result, an optimal adjusting framework is proposed to address the noise, occlusions, and outliners. Different from the typical multi-view stereo (MVS) methods, the proposed approach not only use the color constraint, but also use the geometric constraint associating multiple frame from the image sequence. The result shows the disparity with a good visual quality that most of the noise is eliminated, the errors in occlusion area are suppressed and the details of scene objects are preserved.
AB - This paper proposes a novel method for estimating disparity accurately. To achieve the ideal result, an optimal adjusting framework is proposed to address the noise, occlusions, and outliners. Different from the typical multi-view stereo (MVS) methods, the proposed approach not only use the color constraint, but also use the geometric constraint associating multiple frame from the image sequence. The result shows the disparity with a good visual quality that most of the noise is eliminated, the errors in occlusion area are suppressed and the details of scene objects are preserved.
KW - Color constraint
KW - Disparity estimation
KW - Geometry constraint
KW - Multi-view stereo (MVS)
UR - http://www.scopus.com/inward/record.url?scp=84924347660&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84924347660&partnerID=8YFLogxK
U2 - 10.1117/12.2180535
DO - 10.1117/12.2180535
M3 - Conference contribution
SN - 9781628415605
VL - 9445
BT - Proceedings of SPIE - The International Society for Optical Engineering
PB - SPIE
ER -