New Evolutions in Video Editing Software and Fantastic Solutions

As online videos are being shared more than ever before due to the rise of social media. Platforms such as Instagram, YouTube, and X, have video editing software can increase likes and followers. While many people may be familiar with common video editing software options such as Adobe Premiere; there are now many automatic machine-learning video editors and enhancement softwares available.

With these video editing offerings, consumers can now easily edit hours of video footage easily and affordably. However, many people may still be wondering about the particulars of traditional video editing, from its definition to its applications. What’s more, consumers may also be wondering what the differences are when comparing traditional video editing to machine learning software.

Defining video editing

Video editing is defined as the process of manipulating recorded video footage; most often for release to the general public in some form or fashion. Video editing is used to structure and format all forms of video content; ranging from television shows to advertisements that run during commercial breaks. Many forms of raw footage will need some type of refinement, like color correction or cropping. Other common video editing functions include:

• Exposure adjustment
• Blurring
• Trimming
• Re-sequencing
• Cut-aways
• Fade out/fade in
• Cross dissolving

While video editing sounds self-explanatory there is more to it. In post-production, edits like sound design and CGI are completed; after the bulk of video editing is finished. Contemporary video editing derives from analog recording or film splicing practices. In which audio signals are directly stored in a physical medium using mechanical systems such as the phonograph and phonautograph. While these analog methods were effective in delivering a quality end product, the process and costs involved made most video editing techniques impractical for the everyday working person.

Video editing in the past

Video editing in the 1950s often involved visualization. Using ferrorfluid, a liquid that is attracted to the pole of magnents to show the recording track. After using ferrorfluid, the track would be cut with a guiillotine cutter or razor blade.

Analog recording practices hinge on exact replication of the original sound waves. However, this can cause complications. As such, editing a single video could take days if not weeks since the process had to be done manually. Splicing machines were created to aid this process but were expensive and complicated. This limited their users to students and professionals for the most part.

In response to this, linear editing methods began to be developed in the 1970s and 1980s. Linear editing works by selectively copying one video to another through two connected machines. With one machine acting as a source and the other as the recorder. This form of video editing was easier than splicing. However, a different set of complications arose.

Linear editing requires work to occur in a forward fashion. This eliminated the option to correct any mistakes after completion. As such, a barrier still existed in regards to consumers being able to engage in the video editing process.

Modernizing video editing

As evolution continued, video editing was computerized in the 1990s, making it widely available for the first time. Digital video editing works by replicating a sample of a video; as opposed to copying the entirity as with analog and linear editing. Additionally, digitial video editing programs could be used in a non-linear fashion. This greatly cut down on video editing times.

Despite advancements in digital editing, early video editing software offerings still required a certain level of expertise and skill to be adequately used. Furthermore, there was a certain level of computer literacy that was needed to operate the machines that these software programs ran on. Additionally, these computers and software programs could prove to be very costly, as they were forms of technology that were very new to the consumer market in the early to mid-1990s. As such, video editing for the everyday working person did not truly become feasible until recent years, with the advent of automatic video editing software that took out much of the expertise involved and greatly lowered the cost.

What different types of video editing software are there?

With the rise of digital recording techniques replacing traditional analog methods, automatic video software options that could automate this process became more common. What’s more, the rise of smartphone applications has allowed for video editing software to be used via smartphones and tablets as opposed to only personal computers. The prices for these options will range anywhere from a monthly subscription to a yearly license fee, depending on the specific automatic video editing needs of the person or company looking to purchase the software. Common examples of video editing software include:

• Adobe Premiere Rush
• Adobe Premiere Pro
• CaseGuard Studio
• Apple iMovie
• Windows Movie Maker
• Vimeo
• YouTube
• Davinci Resolve
• Avid Media Composer

Machine Learning Video Editing Software

As opposed to traditional video editing methods, automatic video editing software options allow average consumers to easily and effortlessly edit videos from the comfort of their homes or offices. These programs work by allowing users to select from a certain list of editing or visual effects and the video will be automatically edited.

Additionally, these programs will also provide users with a percentage-based confidence level concerning the effectiveness of the automatic video editing process. With this confidence level, users can still go back and make edits manually after the automation process has concluded to achieve the greatest possible results.

These automatic video editing software programs function based on machine learning techniques. Through these machine learning techniques, such as object detection, object tracking, smart resolution, and machine learning enhancement and redaction options, processes that would have taken days to complete manually can now be completed in a matter of minutes.

For example, object detection will automatically detect the presence of certain objects within video recordings, as opposed to having to manually scan a recording for certain faces, people, or other forms of objects. Alternatively, object detection along with enhancements effects such as the sharpen and contrast effects can be used to improve the pixelate and brightness of colors in video recordings respectively. With these machine learning techniques, the everyday user can now tackle the video editing process without having to feel like they are out of their depth.

As artificial intelligence and machine learning techniques have pushed the boundary on what can be accomplished through technology, video editing software programs can now accomplish more than ever before. New machine learning features such as automatic object detection and video enhancement techniques allow for users to edit their videos in the most efficient manner as possible, by greatly lowering the level of skill needed to make edits to video content. Through these means, people in all types of businesses can now effectively edit video recordings and content without having to spend an excessively high amount of money or engage in a complicated or confusing process.