Details
| Originalsprache | Englisch |
|---|---|
| Titel des Sammelwerks | 2009 IEEE International Conference on Acoustics, Speech, and Signal Processing |
| Untertitel | Proceedings |
| Seiten | 773-776 |
| Seitenumfang | 4 |
| Publikationsstatus | Veröffentlicht - Mai 2009 |
| Veranstaltung | 2009 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2009 - Taipei, Taiwan Dauer: 19 Apr. 2009 → 24 Apr. 2009 |
Publikationsreihe
| Name | ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings |
|---|---|
| ISSN (Print) | 1520-6149 |
Abstract
Cast shadows cause serious problems in the functionality of vision-based applications, such as video surveillance, traffic monitoring and various other applications. Accurate detection and removal of cast shadows is a challenging task. Common shadow detection techniques normally use color information, which is not a reliable base in every scenario. This paper presents a novel scheme for real time detection of cast shadows using contour like structures of objects, which are obtained by gradient-based background subtraction. The scheme does not use any color information. Two basic rules are followed for shadow detection. The first rule is that shadows do not change the texture of the background. The second rule is a cast shadow lies outside the boundary of an object and has a relatively small common boundary with the object. Experimental results show the performance of the proposed scheme. Objective evaluation shows that the algorithm classifies 90 percent of the pixels of the objects and their shadow correctly.
ASJC Scopus Sachgebiete
- Informatik (insg.)
- Software
- Informatik (insg.)
- Signalverarbeitung
- Ingenieurwesen (insg.)
- Elektrotechnik und Elektronik
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- BibTex
- RIS
2009 IEEE International Conference on Acoustics, Speech, and Signal Processing : Proceedings. 2009. S. 773-776 4959698 (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings).
Publikation: Beitrag in Buch/Bericht/Sammelwerk/Konferenzband › Aufsatz in Konferenzband › Forschung › Peer-Review
}
TY - GEN
T1 - Shadow detection for moving humans using gradient-based background subtraction
AU - Shoaib, Muhammad
AU - Dragon, Ralf
AU - Ostermann, Jörn
PY - 2009/5
Y1 - 2009/5
N2 - Cast shadows cause serious problems in the functionality of vision-based applications, such as video surveillance, traffic monitoring and various other applications. Accurate detection and removal of cast shadows is a challenging task. Common shadow detection techniques normally use color information, which is not a reliable base in every scenario. This paper presents a novel scheme for real time detection of cast shadows using contour like structures of objects, which are obtained by gradient-based background subtraction. The scheme does not use any color information. Two basic rules are followed for shadow detection. The first rule is that shadows do not change the texture of the background. The second rule is a cast shadow lies outside the boundary of an object and has a relatively small common boundary with the object. Experimental results show the performance of the proposed scheme. Objective evaluation shows that the algorithm classifies 90 percent of the pixels of the objects and their shadow correctly.
AB - Cast shadows cause serious problems in the functionality of vision-based applications, such as video surveillance, traffic monitoring and various other applications. Accurate detection and removal of cast shadows is a challenging task. Common shadow detection techniques normally use color information, which is not a reliable base in every scenario. This paper presents a novel scheme for real time detection of cast shadows using contour like structures of objects, which are obtained by gradient-based background subtraction. The scheme does not use any color information. Two basic rules are followed for shadow detection. The first rule is that shadows do not change the texture of the background. The second rule is a cast shadow lies outside the boundary of an object and has a relatively small common boundary with the object. Experimental results show the performance of the proposed scheme. Objective evaluation shows that the algorithm classifies 90 percent of the pixels of the objects and their shadow correctly.
KW - Background subtraction
KW - Shadows
KW - Video surveillance
UR - http://www.scopus.com/inward/record.url?scp=70349200921&partnerID=8YFLogxK
U2 - 10.1109/ICASSP.2009.4959698
DO - 10.1109/ICASSP.2009.4959698
M3 - Conference contribution
AN - SCOPUS:70349200921
SN - 9781424423545
T3 - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
SP - 773
EP - 776
BT - 2009 IEEE International Conference on Acoustics, Speech, and Signal Processing
T2 - 2009 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2009
Y2 - 19 April 2009 through 24 April 2009
ER -