We propose a novel supervised learning technique for summarizing videos by automatically
selecting keyframes or key subshots. Casting the task as a structured prediction problem …

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 technique to create a short skim of the original video while
preserving the main stories/content. There exists a substantial interest in automatizing this …

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 …

Recently, increasing attention has been paid to the detection of spatio-temporal interest
points (STIPs), which has become a key technique and research focus in the field of …

We consider the problem of video summarization. Given an input raw video, the goal is to
select a small subset of key frames from the input video to create a shorter summary video …

The goal of video summarization is to distill a raw video into a more compact form without
losing much semantic information. However, previous methods mainly consider the diversity …

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

Video skimming, also known as dynamic video summarization, generates a temporally
abridged version of a given video. Skimming can be achieved by identifying significant …

Recent years have witnessed a resurgence of interest in video summarization. However,
one of the main obstacles to the research on video summarization is the user subjectivity …