Title :
Resource restricted on-line Video Summarization with Minimum Sparse Reconstruction
Author :
Shaohui Mei ; Zhiyong Wang ; Mingyi He ; Dagan Feng
Author_Institution :
Sch. of Electron. & Inf., Northwestern Polytech. Univ., Xi´an, China
fDate :
May 31 2015-June 3 2015
Abstract :
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.
Keywords :
computational complexity; video retrieval; video signal processing; RR-onMSR; minimum sparse reconstruction; online minimum sparse reconstruction based VS algorithm; resource restricted OnMSR algorithm; resource restricted applications; resource restricted online video summarization; retrieval applications; video based analysis complexity; video content representation; Algorithm design and analysis; Clustering algorithms; Image reconstruction; Multimedia communication; Pattern recognition; Real-time systems; Streaming media;
Conference_Titel :
Picture Coding Symposium (PCS), 2015
Conference_Location :
Cairns, QLD
DOI :
10.1109/PCS.2015.7170063