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