TY - GEN
T1 - Background subtraction using spatio-temporal continuities
AU - Varadarajan, Srenivas
AU - Karam, Lina
AU - Florencio, Dinei
PY - 2010/12/1
Y1 - 2010/12/1
N2 - This paper presents a novel scheme for dynamically recovering a background image from consecutive frames of a video sequence based on spatial and temporal continuities. The proposed background subtraction algorithm applies a boundary-level spatial continuity constraint in order to detect and correct ghosting, which corresponds to incorrectly classified foreground regions due to fast moving objects. A pixel-level spatial continuity metric that effectively recovers regions with partial ghosting problems is also proposed in this paper together with a selective application of a temporal continuity metric in order to prevent strong pixel transitions in the background from hindering the background recovery process. The proposed method can also be applied successfully to sequences with deformable foreground objects and non-uniform motion. Simulation results show that the extracted background, when used for foreground detection, results in a higher performance in terms of recall and precision as compared to existing popular schemes.
AB - This paper presents a novel scheme for dynamically recovering a background image from consecutive frames of a video sequence based on spatial and temporal continuities. The proposed background subtraction algorithm applies a boundary-level spatial continuity constraint in order to detect and correct ghosting, which corresponds to incorrectly classified foreground regions due to fast moving objects. A pixel-level spatial continuity metric that effectively recovers regions with partial ghosting problems is also proposed in this paper together with a selective application of a temporal continuity metric in order to prevent strong pixel transitions in the background from hindering the background recovery process. The proposed method can also be applied successfully to sequences with deformable foreground objects and non-uniform motion. Simulation results show that the extracted background, when used for foreground detection, results in a higher performance in terms of recall and precision as compared to existing popular schemes.
KW - Background extraction
KW - Motion
KW - Object removal
KW - Occlusion removal
KW - Video
UR - http://www.scopus.com/inward/record.url?scp=79951619400&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=79951619400&partnerID=8YFLogxK
U2 - 10.1109/EUVIP.2010.5699142
DO - 10.1109/EUVIP.2010.5699142
M3 - Conference contribution
AN - SCOPUS:79951619400
SN - 9781424472871
T3 - 2010 2nd European Workshop on Visual Information Processing, EUVIP2010
SP - 144
EP - 148
BT - 2010 2nd European Workshop on Visual Information Processing, EUVIP2010
T2 - 2nd European Workshop on Visual Information Processing, EUVIP2010
Y2 - 5 July 2010 through 7 July 2010
ER -