Artificial intelligence provides a lead forward in content creation, distribution, and archiving

Artificial intelligence provides a lead forward in content creation, Digital nirvana video intelligence using Monitoriq product

As artificial intelligence capabilities rapidly evolve, it promises to transform the media and entertainment industry from content creation to distribution and enhanced user experience. The influence it exercises on the industry helps content creators become more creative, content editors become more productive, and content consumers reap the benefits of both by being able to find the content that matches their interest. Video Intelligence is evolving every day and is a vast concept altogether. The media industry embraces various facets of video intelligence and knits it with content production that enhances overall viewer experience. In this blog, let’s talk about some video intelligence features that have a great impact on content production.

Facial Recognition: Identifying a character on-screen is a video intelligence feature. OTT streaming platforms like Amazon’s Rekognition provide highly accurate facial analysis and facial recognition on videos provided. The feature helps identify the character on-screen you wouldn’t mind knowing more about. The celebrity recognition feature identifies well known people in a wide range of categories from the video and image libraries.

Digital Nirvana Monitoriq video intelligence features shot change detection, face recognition and object identification

Content moderation: It is important to deliver appropriate and age-approved content to the user, but manual content review to recognize faulty content is a tedious process. Content moderation, a significant part of video intelligence, monitors content and lets the content producer sort content that is irrelevant, obscene, illegal, and/or insulting. This feature helps in detecting objectionable content in all forms, in all types of videos including animations, and alerts the user of the presence of inappropriate content.

Content-based Recommendation: Content recommendation is another smart feature of video intelligence where, depending on viewer preferences, content can be recommended. One feature of YouTube is to “suggest videos” to users based on what they have viewed in the past, improving user engagement. Streaming platforms like Netflix also recommend videos based on viewer preferences. For example, if the viewer’s favorite subject is History, Netflix suggests more content pertaining to that particular genre.

Media archives: Content with enhanced metadata is an important aspect of the broadcast industry. Content producers these days need to produce more content fast. Metadata creation via cloud Video Intelligence helps create indexed media archives of your video library by using the metadata from the video intelligence API and keeps a track of the content generated. Create an indexed archive of your entire video library by using the metadata from Video Intelligence API.

Text detection and speech transcription: Enhancing video accessibility by adding captions/subtitles to video assets is important. Content owners prefer adding automatic transcripts to the content. Identifying on-screen text enriches content quality and enhances end-user experience.

Character and object detection: Identifying characters and objects on screen has become one of the most talked-about features of video intelligence. This feature helps identify the breed of the adorable dog on-screen. There is a scope of expansion in terms of being able to identify the behavior and sentiment of the characters on screen and also predict their future moves. This futuristic development could be a great boon for those in the media industry as editing videos and searching for specific segments will be easier than ever. In fact, upon freezing a frame, all objects visible in the frame can also be identified.

AutoML: A service offered by Google, now gives users access to its trove of data to help us identify and label the uploaded content by matching it with what’s available in the database. Upon uploading our own photos, it helps us compare them with its database and relevantly label them. If, after a recent trip to the jungle, you’ve uploaded photographs of wildlife, the feature will help identify and tag animals and flowers by name as long as it’s available in the database.

Shot change detection: Videos are basically a collaboration of multiple images. A collection of pictures make a shot, a collaboration of shots is a scene, and a collaboration of scenes is a video clip. An essential step in video content analysis, this feature recognizes objects and scenes from a series of frames representing the same objects with continuous actions in time and space.

Regionalization: This feature of video intelligence helps identify the location of the shoot. In a video that involves clippings from multiple areas, this feature could be of great help.

Video Intelligence enhances content quality and makes content production easier and more efficient. It reduces the time and effort to create more meaningful content and gives viewers detailed information, bettering user experience.

Digital Nirvana’s MonitorIQ, the next-gen broadcast monitoring and compliance logging platform, provides access to AI-based cloud microservices with its Media Services Portal, integrated with a video intelligence engine for logo detection, object identification, face recognition, and shot change detection amongst others.