Depth Perception from a 2D Natural Scene Using Scale Variation of Texture Patterns

Yousun KANG  Hiroshi NAGAHASHI  

IEICE TRANSACTIONS on Information and Systems   Vol.E89-D   No.3   pp.1294-1298
Publication Date: 2006/03/01
Online ISSN: 1745-1361
DOI: 10.1093/ietisy/e89-d.3.1294
Print ISSN: 0916-8532
Type of Manuscript: LETTER
Category: Pattern Recognition
depth perception,  texture gradient,  hierarchical discriminant analysis,  autocorrelation functions,  

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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.