DocumentCode :
3149546
Title :
Shape from point features
Author :
Gu, Steve ; Zheng, Ying ; Tomasi, Carlo
Author_Institution :
Dept. of Comput. Sci., Duke Univ., Durham, NC, USA
fYear :
2012
fDate :
25-30 March 2012
Firstpage :
1425
Lastpage :
1428
Abstract :
We present a nonparametric and efficient method for shape localization that improves on the traditional sub-window search in capturing the fine geometry of an object from a small number of feature points. Our method implies that the discrete set of features capture more appearance and shape information than is commonly exploited. We use the a-complex by Edelsbrunner et al. to build a filtration of simplicial complexes from a user-provided set of features. The optimal value of a is determined automatically by a search for the densest complex connected component, resulting in a parameter-free algorithm. Given K features, localization occurs in O(K log K) time. For VGA-resolution images, computation takes typically less than 10 milliseconds. We use our method for interactive object cut, with promising results.
Keywords :
image resolution; image segmentation; shape recognition; VGA-resolution images; a-complex; feature points; fine geometry; nonparametric method; parameter-free algorithm; point features; shape information; shape localization; sub-window search; Distance measurement; Image color analysis; Object recognition; Search problems; Shape; Support vector machine classification; Visualization; alpha shapes; object segmentation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics, Speech and Signal Processing (ICASSP), 2012 IEEE International Conference on
Conference_Location :
Kyoto
ISSN :
1520-6149
Print_ISBN :
978-1-4673-0045-2
Electronic_ISBN :
1520-6149
Type :
conf
DOI :
10.1109/ICASSP.2012.6288158
Filename :
6288158
Link To Document :
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