There is an abundance of video content online. While texts can be easily skimmed through to see if there are any relevant topics, videos make this impossible.
Therefore, knowing how to summarize a video clip while retaining the key footage would be a truly life-saving tool. The application and possibilities are really limitless.
This article is a quick guide to help you learn more about summarizing long videos.
For example, consider surveillance videos, where the same content repeats for hours on end. And you need to swiftly access the brief moments when something happens.
The advancement in artificial intelligence, natural language processing, machine learning, and image processing is giving rise to some automatic video summarizing tools. Though the tools are not all perfect and require some human intervention, it’s gradually getting there!
What Is the Importance of Video Summary?
A video summary is a concise and condensed version of the information contained in a larger video document. It picks up the most informative and interesting segments of the video content for the viewers.
Typically, the output summary consists of a group of keyframes or video clips that were removed from the original video. The aim of video summarization is to facilitate efficient access to video content while accelerating browsing through a massive collection of video data.
Users can quickly assess the value and usefulness of the video by viewing the summary. Usability studies are frequently used to evaluate summaries. They assess the information quality of the material based on the applications and target users.
How to Summarize a Video Clip?
Video summarization is similar to when you automatically summarize a text. To summarize a video clip, you must break it down into smaller parts and choose the most relevant parts to include in the summary.
The goal is to create a more compact and shorter video than the original while retaining the key information. The final video output must be clearly and easily understandable.
In general, video summarization algorithms extract image attributes from video frames. It then employs neural network technologies to select the most relevant frames by analyzing the visual variations between the extracted image features. You can achieve this by two primary methods, which are:
- Obtaining sets of static keyframes from the original video clip, known as keyframing.
- Extracting groups of shots with audio and motion. We call this process video skimming.
More About the Two Video Summarizing Methods
A video summary generated using a video skimming technique is undoubtedly more entertaining than one obtained by keyframing. Video skimming creates a video that resembles a real video using temporal concatenation, consistent audio, and more.
In both cases, be they shots or frames, the videos are analyzed and grouped in a set by similarity, and redundant ones are removed. For example, in video frames, the existence of the same color or object in the images is evaluated.
The procedure can also be done under human supervision, in which case the training sets are labeled by people. And the outcome is more accurate even if it requires more time and work. Another strategy is to figure out the essential points of the video from its subtitles.
The internet is filled with video content. And sometimes, it becomes necessary to get the gist of lengthy videos without having to watch the entire video clip.
Therefore, summarizing video clips is important. Learning how to summarize a video clip is an easy process, thanks to the advancement of artificial intelligence tools.
Video summarization is done using different methods. This guide discusses the importance of video summaries and the mechanism behind the procedures.
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