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Structured Sparse Coding With the Group Log-regularizer for Key Frame Extraction
- Source :
- IEEE/CAA Journal of Automatica Sinica; 2022, Vol. 9 Issue: 10 p1818-1830, 13p
- Publication Year :
- 2022
-
Abstract
- Key frame extraction based on sparse coding can reduce the redundancy of continuous frames and concisely express the entire video. However, how to develop a key frame extraction algorithm that can automatically extract a few frames with a low reconstruction error remains a challenge. In this paper, we propose a novel model of structured sparse-coding-based key frame extraction, wherein a nonconvex group log-regularizer is used with strong sparsity and a low reconstruction error. To automatically extract key frames, a decomposition scheme is designed to separate the sparse coefficient matrix by rows. The rows enforced by the nonconvex group log-regularizer become zero or nonzero, leading to the learning of the structured sparse coefficient matrix. To solve the nonconvex problems due to the log-regularizer, the difference of convex algorithm (DCA) is employed to decompose the log-regularizer into the difference of two convex functions related to the <tex>$I_{1}$</tex> norm, which can be directly obtained through the proximal operator. Therefore, an efficient structured sparse coding algorithm with the group log-regularizer for key frame extraction is developed, which can automatically extract a few frames directly from the video to represent the entire video with a low reconstruction error. Experimental results demonstrate that the proposed algorithm can extract more accurate key frames from most SumMe videos compared to the state-of-the-art methods. Furthermore, the proposed algorithm can obtain a higher compression with a nearly 18% increase compared to sparse modeling representation selection (SMRS) and an 8% increase compared to SC-det on the VSUMM dataset.
Details
- Language :
- English
- ISSN :
- 23299266 and 23299274
- Volume :
- 9
- Issue :
- 10
- Database :
- Supplemental Index
- Journal :
- IEEE/CAA Journal of Automatica Sinica
- Publication Type :
- Periodical
- Accession number :
- ejs60810555
- Full Text :
- https://doi.org/10.1109/JAS.2022.105602