It appears that many of us like to watch videos for all kinds of reasons. It’s a great way to have fun, spend some time, and even learn something new.
And with 5G becoming increasingly available, we can expect a lot more traffic pouring towards video content consumption.
But let’s be honest, ain’t nobody paying you for being on YouTube all day. You still have your life to keep together.
But how do you enjoy all of the great video content out there and not waste time on something less important?
The answer is video summarization. You watch a short compilation, get the information you need, and either proceed to watch the whole thing or move on.
All of that comes after the media companies get to creating video summaries. Let’s talk about how they can do it effectively with video cutting software .
Video content marketing gets long
Media companies get very creative with video content to promote a product, a service, or a piece of media.
Apart from more traditional short-form content like trailers and TV commercials, the show-related promotion is now accompanied by… podcasts?
It should not come as a surprise, though.
Many people listen to long-form content rather than watch it. As we mentioned before, not everybody can dedicate a couple of hours to watch an interview or show’s creators talk about the shooting process or something of that sort.
But it’s no problem if you’re just listening to the thing. You can do dishes, commute to work, workout, take a stroll, or do whatever else.
The stats back the notion up. In the US alone, around 62% of the population has listened to at least one podcast episode, and 40% do that on a somewhat regular basis.
So, we have standalone podcast shows that are doing pretty well, so it is only natural that media companies would start their own shows to promote the other content they are producing.
And those are what they call “companion podcasts”.
Everybody seems to have one of those now. News agencies launch podcasts alongside their written and video coverage of the events that happen every day. Influencers launch their own shows as a secondary stream of content.
And then there are TV shows. As it appears, people do like to know more about the creative process of their favorite series: cast experiences, the writing, video production, location scouting, and many other aspects make up for a good story.
All of that on top of trailers and best moments clips created with video trimming software.
Story that is best told and heard as a podcast.
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Promotion needs more promotion
Just like history, content promotion also likes to repeat itself.
You got a new TV show released on your streaming platform.
And you want to promote it.
So, you make more content that helps you do that. That means using video cutting tools to make trailers, shooting advertisements with the cast, and all the other short-form content you can come up with.
And, as we have discussed, long-form content creation comes in here. Just before the show airs and then as it carries on, you can release the podcast episodes to hype up the show and keep the interest as high as possible.
But hear me out now.
Those podcasts and whatnot also have to be discovered in some way, right?
So you also promote that content as well.
Let’s sum this up.
You make podcasts, or produce companion podcasts to promote your first-party content, like TV shows.
You want them to be discovered by people on the internet.
How do you promote them in the most effective way, knowing that long-form content is hard to commit to from the audience's perspective?
The answer is: video summarization.
Video summarization: cut your viewers some slack. And time
Summarization is a great way to encourage people to discover new long-form content, and bring you the engagement numbers even if they don’t listen to your interviews or podcasts.
Let’s be honest, not a lot of people are ready to jump headfirst into a lengthy piece of content without knowing a single thing about it.
Or they can just be short on time. And then they find all of those episodes, video essays, and interviews piled up in “watch later” playlists.
And none of the content you worked so hard to make gets watched or listened to.
A summary is a great way to bridge the gap between those viewers and your content.
A video summary contains the most important point of the footage or an audio. This way, the viewer can look at a short clip and decide if they’re interested in that particular piece of content.
And you can deliver the summary in many ways, actually. Put them on Instagram newsfeed, Reels or Stories, make TikToks, or just have it roll before the podcast or a video.
That is how you both win: viewers can engage with short-form summaries, and then, if they feel compelled, proceed to enjoy the full-length podcasts. And from your end, you spend little to no time and resources on summarizing videos with the help of video cutting software.
So it’s, like, additional content almost for free.
Let’s talk about that free part.
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How to summarize a video clip: video cutting software
Let’s look at each method of video summarization and see what they offer.
Manual video trimming
You guessed it: sit at the desk, fire up your computer, launch the video cutting software, take the footage, and start cutting away.
Provided you already know the best parts to cut, of course. Otherwise, you will have to rewatch the whole thing to see what parts will make it into the summary.
That’s the biggest drawback of manual video trimming tools. It takes an enormous amount of time to summarize the clips, and you can forget it if you’re working on a large scale with enormous volumes of content.
In this case, you’re looking at hiring a lot of editors.
And special video cutting apps won’t help you either. Basically, those are primitive video editing apps with the set of features that cater the best to compiling the most important moments of lengthy footage.
Switching from more traditional means won’t make much of a difference, to be honest.
AI video cutting software
Now we’re talking: automating the process of video summarization will allow you to save a lot of production resources. And you still end up with more content to share and promote.
But here’s the question: can AI do that?
Sure can. But not in the way you think.
The thing is that AI can’t tell if something is important or not. It can detect emotions, tension, or any other abstract things that we naturally experience as humans.
So, engineers teach AI video cutting software to focus on more perceivable clues, like music, keywords, or audible and visible features that can indicate an important moment.
For instance, AI can look for audience cheering, show host mentioning the topic of conversation, or a guest appearing in the center of the scene.
But those features, despite being somewhat descriptive, do not fully define a moment of interest. Because of that, an AI video trimming tool requires supervision from a human editor to make sure it selects the right clips for a summarization video.
You know what I’m saying next.
Human supervision — more time spent on supervising and correcting mistakes.
We can do better than that.
Video trimming tool powered by cognitive computing
To get the coherent video summarization, we need the software to understand the content on another level. On a human level.
So why are we tinkering with Artificial Intelligence?
Let’s get the real thing — the software that imitates human cognitive abilities.
Cognitive computing can do that, you know. Hence the name.
The video trimming software powered by cognitive computing is miles ahead of its AI counterparts because it can actually understand the content it analyzes. This way it extracts relevant data and makes informed decisions.
Facilitating all of its abilities, there is a set of complex tech baked in:
- Deep learning, digital image processing, and cognitive computer vision enable the software to thoroughly analyze the content and pick up anything of importance;
- Cognitive science, probabilistic AI, machine perception, and math modeling support the decision-making. That’s where the video trimming tool decides which clips make it into the summary.
Thanks to a deeper understanding of the context, cognitive video summarization provides more consistent results and does not require training.
That translates into less time dedicated to summarizing the video:
- You don’t have to train the software for a specific case;
- You don’t need to oversee and correct the output.
You just feed it the video, get your summary, and go on.
And if need arises, you can scale the software to work with whatever volume of content you have. Feed hours of video, get the results in minutes.
Supercharge your video summarization with cognitive computing
It turns out that we like to engage with long-form content. And those are not just binge-fests of Stranger Things or Squid Game, but also podcasts, online interviews, video essays, and so on.
And the rate at which that content appears on the web is only increasing: companies that produce movies and TV shows launch their companion podcasts for promotion, media websites have shows covering the latest news, and influencers are basically interviewers now.
But long-form is kinda long, right? You can’t just chug those episodes down like TikToks.
That’s where summarization comes into play. It allows media companies to promote that content that promotes their other content on platforms that house short-form content, like aforementioned TikTok, or Instagram Reelz and Stories.
The viewers, on the other hand, get the chance to see what the content they’re discovering is about. If they like, they can go on and listen or watch it. If they don’t — well they still have engaged with the summary, right? You get your numbers anyway.
If we’re talking about optimizing content promotion, we also must explore ways to make the content generation as efficient as possible. Obviously, online video cutting apps aren’t that efficient as they appear to be just stripped down versions of basic video editing software.
So, automation it is.
But AI also doesn’t do it. It cannot provide consistent results and requires a lot of time for training and oversight.
That’s why imitating the way humans perceive video content makes the most sense. So, cognitive computing is our best option. It doesn’t need training, it can easily be scaled to work with big volumes of data, and it automates not only the analysis but also the decision making.
Our system guarantees to find the balance between the length of a compilation and its saturation, including the moments with the highest score of intensity.
For Live RTMP Ingest the stream timecodes could be added into meta output for proper syncronization.
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