TY - JOUR
T1 - DFP-ALC
T2 - Automatic video summarization using Distinct Frame Patch index and Appearance based Linear Clustering
AU - Kannappan, Sivapriyaa
AU - Liu, Yonghuai
AU - Tiddeman, Bernie
N1 - Funding Information:
The first author is grateful for the award given by Aberystwyth University under the Departmental Overseas Scholarship (DOS) and partly funding by Object Matrix, Ltd on the project. We are also grateful to the anonymous reviewers for their insightful comments that have improved the clarity and the readability of the paper.
Publisher Copyright:
© 2018
PY - 2019/4/1
Y1 - 2019/4/1
N2 - Video summarization aims to create a succinct representation of videos for efficient browsing and retrieval. We propose an innovative method for the task. It includes two main steps: (i) the first step proposes a Distinct Frame Patch (DFP) index for selecting a set of good candidate frames, and (ii) the second step proposes a novel Appearance based Linear Clustering (ALC) to refine them for distinct ones. While the first step measures the content of frames, the second step considers to what extent one frame is different from another in both the spatial and temporal spaces. The experiments are performed over two publicly accessible datasets. The results show the effectiveness and efficiency of the proposed method when compared with other state-of-the-art techniques.
AB - Video summarization aims to create a succinct representation of videos for efficient browsing and retrieval. We propose an innovative method for the task. It includes two main steps: (i) the first step proposes a Distinct Frame Patch (DFP) index for selecting a set of good candidate frames, and (ii) the second step proposes a novel Appearance based Linear Clustering (ALC) to refine them for distinct ones. While the first step measures the content of frames, the second step considers to what extent one frame is different from another in both the spatial and temporal spaces. The experiments are performed over two publicly accessible datasets. The results show the effectiveness and efficiency of the proposed method when compared with other state-of-the-art techniques.
KW - Appearance based Linear clustering
KW - Bayesian information criterion
KW - Candidate frame selection
KW - Distinct frame patch index
KW - Keyframe extraction
KW - Video summarization
UR - http://www.scopus.com/inward/record.url?scp=85059165365&partnerID=8YFLogxK
U2 - 10.1016/j.patrec.2018.12.017
DO - 10.1016/j.patrec.2018.12.017
M3 - Article
SN - 0167-8655
VL - 120
SP - 8
EP - 16
JO - Pattern Recognition Letters
JF - Pattern Recognition Letters
ER -
