Sciweavers

Share
ICIP
1997
IEEE

Wavelet features for statistical object localization without segmentation

12 years 1 months ago
Wavelet features for statistical object localization without segmentation
This paper describes a new technique for statistical 3{D object localization. Local feature vectors are extracted for all image positions, in contrast to segmentation in classical schemes. We de ne a density function for those features and describe a hierarchical pose estimation scheme for the localization of a single object in a scene with arbitrary background. We show how the global pose search on the starting level of the hierarchy can be computed e ciently. The paper compares di erent wavelet transformations used for feature extraction.
Heinrich Niemann, Josef Pösl
Added 26 Oct 2009
Updated 26 Oct 2009
Type Conference
Year 1997
Where ICIP
Authors Heinrich Niemann, Josef Pösl
Comments (0)
books