This paper addresses the problem of unsupervised video summarization, formulated as
selecting a sparse subset of video frames that optimally represent the input video. Our key …

We present a video summarization approach for egocentric or “wearable” camera data.
Given hours of video, the proposed method produces a compact storyboard summary of the …

We present a video summarization approach that discovers the story of an egocentric video.
Given a long input video, our method selects a short chain of video subshots depicting the …

Video summarization is a challenging problem with great application potential. Whereas
prior approaches, largely unsupervised in nature, focus on sampling useful frames and …

Video summarization has unprecedented importance to help us digest, browse, and search
today's ever-growing video collections. We propose a novel subset selection technique that …

We propose a principled approach to summarization of visual data (images or video) based
on optimization of a well-defined similarity measure. The problem we consider is re-targeting …

Given the enormous growth in user-generated videos, it is becoming increasingly important
to be able to navigate them efficiently. As these videos are generally of poor quality …

Watching a 360° sports video requires a viewer to continuously select a viewing angle,
either through a sequence of mouse clicks or head movements. To relieve the viewer from …

With the widespread availability of video cameras, we are facing an ever-growing enormous
collection of unedited and unstructured video data. Due to lack of an automatic way to …

Supervised learning techniques have shown substantial progress on video summarization.
State-of-the-art approaches mostly regard the predicted summary and the human summary …