DocumentCode :
3410298
Title :
Detecting and sketching the common
Author :
Bagon, Shai ; Brostovski, Ori ; Galun, Meirav ; Irani, Michal
Author_Institution :
Dept. of Comput. Sci. & Appl. Math., Weizmann Inst. of Sci., Rehovot, Israel
fYear :
2010
fDate :
13-18 June 2010
Firstpage :
33
Lastpage :
40
Abstract :
Given very few images containing a common object of interest under severe variations in appearance, we detect the common object and provide a compact visual representation of that object, depicted by a binary sketch. Our algorithm is composed of two stages: (i) Detect a mutually common (yet non-trivial) ensemble of `self-similarity descriptors´ shared by all the input images. (ii) Having found such a mutually common ensemble, `invert´ it to generate a compact sketch which best represents this ensemble. This provides a simple and compact visual representation of the common object, while eliminating the background clutter of the query images. It can be obtained from very few query images. Such clean sketches may be useful for detection, retrieval, recognition, co-segmentation, and for artistic graphical purposes.
Keywords :
image representation; object detection; optimisation; statistical analysis; binary sketch; compact sketch; compact visual representation; mutually common ensemble; object detection; query image; self similarity descriptor; Computer science; Heart; Image databases; Image retrieval; Image segmentation; Information retrieval; Mathematics; Object detection; Shape; Software libraries;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Vision and Pattern Recognition (CVPR), 2010 IEEE Conference on
Conference_Location :
San Francisco, CA
ISSN :
1063-6919
Print_ISBN :
978-1-4244-6984-0
Type :
conf
DOI :
10.1109/CVPR.2010.5540233
Filename :
5540233
Link To Document :
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