Abstract
Background modeling has been widely researched to detect moving objects from image sequences. Most approaches have a falsenegative problem caused by a stopped object. When a moving object stops in an observing scene, it will be gradually trained as background since the observed pixel value is directly used for updating the background model. In this paper, we propose 1) a method to inhibit background training, and 2) a method to update an original background region occluded by stopped object. We have used probabilistic approach and predictive approach of background model to solve these problems. The great contribution of this paper is that we can keep paused objects from being trained.
| Original language | English |
|---|---|
| Title of host publication | Computer Vision - ACCV 2010 Workshops - ACCV 2010 International Workshops, Revised Selected Papers |
| Pages | 12-22 |
| Number of pages | 11 |
| Edition | PART1 |
| DOIs | |
| Publication status | Published - Sep 28 2011 |
| Event | International Workshops on Computer Vision, ACCV 2010 - Queenstown, New Zealand Duration: Nov 8 2010 → Nov 9 2010 |
Publication series
| Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|---|---|
| Number | PART1 |
| Volume | 6468 LNCS |
| ISSN (Print) | 0302-9743 |
| ISSN (Electronic) | 1611-3349 |
Other
| Other | International Workshops on Computer Vision, ACCV 2010 |
|---|---|
| Country | New Zealand |
| City | Queenstown |
| Period | 11/8/10 → 11/9/10 |
Fingerprint
All Science Journal Classification (ASJC) codes
- Theoretical Computer Science
- Computer Science(all)
Cite this
Adaptive background modeling for paused object regions. / Shimad, Atsushi; Yoshinaga, Satoshi; Taniguchi, Rin Ichiro.
Computer Vision - ACCV 2010 Workshops - ACCV 2010 International Workshops, Revised Selected Papers. PART1. ed. 2011. p. 12-22 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6468 LNCS, No. PART1).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Adaptive background modeling for paused object regions
AU - Shimad, Atsushi
AU - Yoshinaga, Satoshi
AU - Taniguchi, Rin Ichiro
PY - 2011/9/28
Y1 - 2011/9/28
N2 - Background modeling has been widely researched to detect moving objects from image sequences. Most approaches have a falsenegative problem caused by a stopped object. When a moving object stops in an observing scene, it will be gradually trained as background since the observed pixel value is directly used for updating the background model. In this paper, we propose 1) a method to inhibit background training, and 2) a method to update an original background region occluded by stopped object. We have used probabilistic approach and predictive approach of background model to solve these problems. The great contribution of this paper is that we can keep paused objects from being trained.
AB - Background modeling has been widely researched to detect moving objects from image sequences. Most approaches have a falsenegative problem caused by a stopped object. When a moving object stops in an observing scene, it will be gradually trained as background since the observed pixel value is directly used for updating the background model. In this paper, we propose 1) a method to inhibit background training, and 2) a method to update an original background region occluded by stopped object. We have used probabilistic approach and predictive approach of background model to solve these problems. The great contribution of this paper is that we can keep paused objects from being trained.
UR - http://www.scopus.com/inward/record.url?scp=80053125931&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=80053125931&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-22822-3_2
DO - 10.1007/978-3-642-22822-3_2
M3 - Conference contribution
AN - SCOPUS:80053125931
SN - 9783642228216
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 12
EP - 22
BT - Computer Vision - ACCV 2010 Workshops - ACCV 2010 International Workshops, Revised Selected Papers
ER -