TY - GEN
T1 - Panning and Jitter Invariant Incremental Principal Component Pursuit for Video Background Modeling
AU - Chau, Gustavo
AU - Rodriguez, Paul
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/7/1
Y1 - 2017/7/1
N2 - Video background modeling is an important preprocessing stage for various applications and principal component pursuit (PCP) is among the state-of-the-art algorithms for this task. One of the main drawbacks of PCP is its sensitivity to jitter and camera movement. This problem has only been partially solved by a few methods devised for jitter or small transformations. However, such methods cannot handle the case of moving or panning cameras. We present a novel, fully incremental PCP algorithm, named incPCP-PTI, that is able to cope with panning scenarios and jitter by continuously aligning the low-rank component to the current reference frame of the camera. To the best of our knowledge, incPCP-PTI is the first low rank plus additive incremental matrix method capable of handling these scenarios. Results on synthetic videos and CDNET2014 videos show that incPCP-PTI is able to maintain a good performance in the detection of moving objects even when panning and jitter are present in a video.
AB - Video background modeling is an important preprocessing stage for various applications and principal component pursuit (PCP) is among the state-of-the-art algorithms for this task. One of the main drawbacks of PCP is its sensitivity to jitter and camera movement. This problem has only been partially solved by a few methods devised for jitter or small transformations. However, such methods cannot handle the case of moving or panning cameras. We present a novel, fully incremental PCP algorithm, named incPCP-PTI, that is able to cope with panning scenarios and jitter by continuously aligning the low-rank component to the current reference frame of the camera. To the best of our knowledge, incPCP-PTI is the first low rank plus additive incremental matrix method capable of handling these scenarios. Results on synthetic videos and CDNET2014 videos show that incPCP-PTI is able to maintain a good performance in the detection of moving objects even when panning and jitter are present in a video.
UR - http://www.scopus.com/inward/record.url?scp=85046283271&partnerID=8YFLogxK
U2 - 10.1109/ICCVW.2017.218
DO - 10.1109/ICCVW.2017.218
M3 - Conference contribution
AN - SCOPUS:85046283271
T3 - Proceedings - 2017 IEEE International Conference on Computer Vision Workshops, ICCVW 2017
SP - 1844
EP - 1852
BT - Proceedings - 2017 IEEE International Conference on Computer Vision Workshops, ICCVW 2017
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 16th IEEE International Conference on Computer Vision Workshops, ICCVW 2017
Y2 - 22 October 2017 through 29 October 2017
ER -