TY - GEN
T1 - Resource restricted on-line Video Summarization with Minimum Sparse Reconstruction
AU - Mei, Shaohui
AU - Wang, Zhiyong
AU - He, Mingyi
AU - Feng, Dagan
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2015/7/28
Y1 - 2015/7/28
N2 - Video Summarization (VS) techniques have been widely utilized to produce a concise video content representation, such that the video content can be quickly explored and the complexity of video based analysis and retrieval applications can be highly reduced. However, little attention has been paid for on-line applications, especially for resource restricted applications, such as onboard VS. In this paper, our previous on-line Minimum Sparse Reconstruction (OnMSR) based VS algorithm is improved for resources restricted applications by confining the size of keyframes for reconstruction. Specially, an on-line reconstruction keyframe set update strategy is designed to meet the requirement of real-time resource restricted situation. Experimental results on various types of videos demonstrate the performance of OnMSR does not vary much by imposing resource constraint in the proposed resource restricted OnMSR (RR-onMSR) algorithm. As a result, the proposed RR-onMSR is very effective for real-time onboard VS applications.
AB - Video Summarization (VS) techniques have been widely utilized to produce a concise video content representation, such that the video content can be quickly explored and the complexity of video based analysis and retrieval applications can be highly reduced. However, little attention has been paid for on-line applications, especially for resource restricted applications, such as onboard VS. In this paper, our previous on-line Minimum Sparse Reconstruction (OnMSR) based VS algorithm is improved for resources restricted applications by confining the size of keyframes for reconstruction. Specially, an on-line reconstruction keyframe set update strategy is designed to meet the requirement of real-time resource restricted situation. Experimental results on various types of videos demonstrate the performance of OnMSR does not vary much by imposing resource constraint in the proposed resource restricted OnMSR (RR-onMSR) algorithm. As a result, the proposed RR-onMSR is very effective for real-time onboard VS applications.
UR - http://www.scopus.com/inward/record.url?scp=84945925006&partnerID=8YFLogxK
U2 - 10.1109/PCS.2015.7170063
DO - 10.1109/PCS.2015.7170063
M3 - 会议稿件
AN - SCOPUS:84945925006
T3 - 2015 Picture Coding Symposium, PCS 2015 - with 2015 Packet Video Workshop, PV 2015 - Proceedings
SP - 139
EP - 143
BT - 2015 Picture Coding Symposium, PCS 2015 - with 2015 Packet Video Workshop, PV 2015 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 31st Picture Coding Symposium, PCS 2015 - with 2015 Packet Video Workshop, PV 2015
Y2 - 31 May 2015 through 3 June 2015
ER -