# Video Summarization in a Multi-View Camera Network

arXiv: https://arxiv.org/abs/1608.00310 · HTML: https://mlsanity.com/paper/1608.00310/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 1 Aug 2016.

## Built on by (most cited first, 1 of 1)

- [Collaborative Multi-Agent Video Fast-Forwarding](https://mlsanity.com/paper/2305.17569/) (2023)

## Abstract (arXiv)

While most existing video summarization approaches aim to extract an informative summary of a single video, we propose a novel framework for summarizing multi-view videos by exploiting both intra- and inter-view content correlations in a joint embedding space. We learn the embedding by minimizing an objective function that has two terms: one due to intra-view correlations and another due to inter-view correlations across the multiple views. The solution can be obtained directly by solving one Eigen-value problem that is linear in the number of multi-view videos. We then employ a sparse representative selection approach over the learned embedding space to summarize the multi-view videos. Experimental results on several benchmark datasets demonstrate that our proposed approach clearly outperforms the state-of-the-art.