IEICE TRANSACTIONS on Information
Depth Perception from a 2D Natural Scene Using Scale Variation of Texture Patterns
Summary :
In this paper, we introduce a new method for depth perception from a 2D natural scene using scale variation of patterns. As the surface from a 2D scene gets farther away from us, the texture appears finer and smoother. Texture gradient is one of the monocular depth cues which can be represented by gradual scale variations of textured patterns. To extract feature vectors from textured patterns, higher order local autocorrelation functions are utilized at each scale step. The hierarchical linear discriminant analysis is employed to classify the scale rate of the feature vector which can be divided into subspaces by recursively grouping the overlapped classes. In the experiment, relative depth perception of 2D natural scenes is performed on the proposed method and it is expected to play an important role in natural scene analysis.
- Publication
- IEICE TRANSACTIONS on Information Vol.E89-D No.3 pp.1294-1298
- Publication Date
- 2006/03/01
- Publicized
- Online ISSN
- 1745-1361
- DOI
- 10.1093/ietisy/e89-d.3.1294
- Type of Manuscript
- LETTER
- Category
- Pattern Recognition
Authors
Keyword
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Yousun KANG, Hiroshi NAGAHASHI, "Depth Perception from a 2D Natural Scene Using Scale Variation of Texture Patterns" in IEICE TRANSACTIONS on Information,
vol. E89-D, no. 3, pp. 1294-1298, March 2006, doi: 10.1093/ietisy/e89-d.3.1294.
Abstract: In this paper, we introduce a new method for depth perception from a 2D natural scene using scale variation of patterns. As the surface from a 2D scene gets farther away from us, the texture appears finer and smoother. Texture gradient is one of the monocular depth cues which can be represented by gradual scale variations of textured patterns. To extract feature vectors from textured patterns, higher order local autocorrelation functions are utilized at each scale step. The hierarchical linear discriminant analysis is employed to classify the scale rate of the feature vector which can be divided into subspaces by recursively grouping the overlapped classes. In the experiment, relative depth perception of 2D natural scenes is performed on the proposed method and it is expected to play an important role in natural scene analysis.
URL: https://global.ieice.org/en_transactions/information/10.1093/ietisy/e89-d.3.1294/_p
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@ARTICLE{e89-d_3_1294,
author={Yousun KANG, Hiroshi NAGAHASHI, },
journal={IEICE TRANSACTIONS on Information},
title={Depth Perception from a 2D Natural Scene Using Scale Variation of Texture Patterns},
year={2006},
volume={E89-D},
number={3},
pages={1294-1298},
abstract={In this paper, we introduce a new method for depth perception from a 2D natural scene using scale variation of patterns. As the surface from a 2D scene gets farther away from us, the texture appears finer and smoother. Texture gradient is one of the monocular depth cues which can be represented by gradual scale variations of textured patterns. To extract feature vectors from textured patterns, higher order local autocorrelation functions are utilized at each scale step. The hierarchical linear discriminant analysis is employed to classify the scale rate of the feature vector which can be divided into subspaces by recursively grouping the overlapped classes. In the experiment, relative depth perception of 2D natural scenes is performed on the proposed method and it is expected to play an important role in natural scene analysis.},
keywords={},
doi={10.1093/ietisy/e89-d.3.1294},
ISSN={1745-1361},
month={March},}
Copy
TY - JOUR
TI - Depth Perception from a 2D Natural Scene Using Scale Variation of Texture Patterns
T2 - IEICE TRANSACTIONS on Information
SP - 1294
EP - 1298
AU - Yousun KANG
AU - Hiroshi NAGAHASHI
PY - 2006
DO - 10.1093/ietisy/e89-d.3.1294
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E89-D
IS - 3
JA - IEICE TRANSACTIONS on Information
Y1 - March 2006
AB - In this paper, we introduce a new method for depth perception from a 2D natural scene using scale variation of patterns. As the surface from a 2D scene gets farther away from us, the texture appears finer and smoother. Texture gradient is one of the monocular depth cues which can be represented by gradual scale variations of textured patterns. To extract feature vectors from textured patterns, higher order local autocorrelation functions are utilized at each scale step. The hierarchical linear discriminant analysis is employed to classify the scale rate of the feature vector which can be divided into subspaces by recursively grouping the overlapped classes. In the experiment, relative depth perception of 2D natural scenes is performed on the proposed method and it is expected to play an important role in natural scene analysis.
ER -
English
