Abstract
This paper addresses the problem of finding glass objects in images. Visual cues obtained by combining the systematic distortions in background texture occurring at the boundaries of transparent objects with the strong highlights typical of glass surfaces are used to train a hierarchy of classifiers, identify glass edges, and find consistent support regions for these edges. Qualitative and quantitative experiments involving a number of different classifiers and real images are presented.
| Original language | English (US) |
|---|---|
| Title of host publication | Proceedings - 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2005 |
| Publisher | IEEE Computer Society |
| Pages | 973-979 |
| Number of pages | 7 |
| ISBN (Print) | 0769523722, 9780769523729 |
| DOIs | |
| State | Published - Jan 1 2005 |
| Event | 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2005 - San Diego, CA, United States Duration: Jun 20 2005 → Jun 25 2005 |
Publication series
| Name | Proceedings - 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2005 |
|---|---|
| Volume | II |
Other
| Other | 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2005 |
|---|---|
| Country | United States |
| City | San Diego, CA |
| Period | 6/20/05 → 6/25/05 |
Fingerprint
ASJC Scopus subject areas
- Engineering(all)
Cite this
Finding glass. / McHenry, Kenton Guadron; Ponce, Jean; Forsyth, David Alexander.
Proceedings - 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2005. IEEE Computer Society, 2005. p. 973-979 1467548 (Proceedings - 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2005; Vol. II).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Finding glass
AU - McHenry, Kenton Guadron
AU - Ponce, Jean
AU - Forsyth, David Alexander
PY - 2005/1/1
Y1 - 2005/1/1
N2 - This paper addresses the problem of finding glass objects in images. Visual cues obtained by combining the systematic distortions in background texture occurring at the boundaries of transparent objects with the strong highlights typical of glass surfaces are used to train a hierarchy of classifiers, identify glass edges, and find consistent support regions for these edges. Qualitative and quantitative experiments involving a number of different classifiers and real images are presented.
AB - This paper addresses the problem of finding glass objects in images. Visual cues obtained by combining the systematic distortions in background texture occurring at the boundaries of transparent objects with the strong highlights typical of glass surfaces are used to train a hierarchy of classifiers, identify glass edges, and find consistent support regions for these edges. Qualitative and quantitative experiments involving a number of different classifiers and real images are presented.
UR - http://www.scopus.com/inward/record.url?scp=24644456086&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=24644456086&partnerID=8YFLogxK
U2 - 10.1109/CVPR.2005.161
DO - 10.1109/CVPR.2005.161
M3 - Conference contribution
AN - SCOPUS:24644456086
SN - 0769523722
SN - 9780769523729
T3 - Proceedings - 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2005
SP - 973
EP - 979
BT - Proceedings - 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2005
PB - IEEE Computer Society
ER -