Better Media Analysis with 5 AI-Based Video Analytics Tools

It is staggering how much video content is created and consumed every single day. 500 hours of video are uploaded to YouTube every minute, according to Statista!

It's obviously difficult for media experts to make sense of anything.

Fortunately, developments in artificial intelligence (AI) have produced potent video analytics tools that quickly and correctly extract important data from videos.

We'll introduce you to the top AI-based video analytics tools available on the market today in this post and demonstrate how you can use them to enhance your media analysis.

What Are Tools for Video Analytics Based on AI?

Progressive CV (Computer Vision) and machine learning technologies are used by AI-based video analytics solutions to extract useful data from videos of all types.

These techniques ideally employ a collection of intricate algorithms that examine films pixel-by-pixel and find actions, objects, and events taking place in real-time or recorded videos.

You can discover information about the items, motions, feelings, and whatever else the algorithms choose. In reality, video analytics solutions allow you to train the algorithms in a variety of ways or even create unique models to meet your company's demands.

Let's say you wish to find objectionable or inappropriate information in uploaded or published videos. On predefined standards explaining what makes information unpleasant or unsuitable for your organization, you can create unique AI models. After that, apply the model on video clips to look for irregularities.

The analytics are based on two fundamental ideas:

• Examines each pixel to find every movement of objects in the movie using motion detection.
• Object recognition: locate and track objects, identify objects that have changed, disappeared, or have appeared recently.

High-end video analytics are mostly utilized in security and surveillance systems to identify and notify users of potential dangers, individuals, or unusual behavior.

Video analytics are widely employed in a variety of industries and provide flexible services tailored to specific business requirements.

However, corporations and media organizations are starting to employ the program more frequently lately.

Brands are using AI-based video analytics solutions in response to the rise in demand for video content to:

• strengthen visual references
• Obtain audience knowledge
• Exploit user-generated content to look for counterfeit goods or phony brand logos

plus a lot more.

Technically speaking, use cases for video analytics systems backed by AI have been developing ever since.

AI-Based Video Analytics Tools: Advantages

1. Detailed Analysis

Advanced video analytics software can perform in-depth analysis on video feeds that is not possible for human eyes to perform.

You see, the brain can interpret visual information that is received by the eye in as little as 13 milliseconds.

We don't expect a human to comprehend every nuance or conflict in streaming media in this brief amount of time. But we can be certain that AI will act in this way.

Instead than analyzing the video as a whole, AI-powered video analytics solutions look at streaming or recorded video frame-by-frame. They can identify, monitor, and classify items in a scene because to the granular methodology.

This level of specificity can be quite helpful in spotting security concerns and unusual activity.

2. Enhanced Productivity and Efficiency

Automation plays a big role in the video analytics process. The technologies can handle everything, from studying films to gathering and storing insights.

In an ideal world, performing these tasks on a daily basis would have required several hours and a huge personnel. You wouldn't be able to obtain the insights that AI would offer, even after many hours of labor.

Let's use an example to clarify this. You have set up a control center to examine the video feed from your physical and mortar store.

Your security team would spend their entire shift staring at the screen without video analytics tools.

However, by combining video analytics, your team will be able to obtain information like:

• best foot traffic
• clients' demographics
• Repeat clients
• Waiting time at the cash register
• The area of the shop where people are most active

You can concentrate on the essential activities, including applying insights to develop plans and improve user experience in your retail shop, because so much data has already been retrieved by analytics tools.

3. Painless Content Modification

Keeping an eye on user-generated content is difficult given the surge in content generation.

You can quickly and easily browse through hours of video content with AI-powered video analytics tools.

The finest aspect is that you can use precise compliance standards to train the algorithm. The program can quickly identify information that does not adhere to the established rules.

In general, video analytics software benefits enterprises by

• Recognize phony brand logos
• Text, audio, and logo references to brands 
• Finding objectionable content

Additionally, it is essential for media outlets to closely check video content. It keeps them from engaging in legal disputes over erroneous brand mentions or disseminating offensive content using their brand name.

4. Instant notifications and alerts

The software can be set up to deliver alerts and notifications if the algorithm discovers something unethical.

This enables content moderators to respond to the alert right away. You can set up alerts for a variety of things, including the detection of bogus logos, out-of-date material, brand references, etc.

In time-sensitive circumstances, particularly in the security industry, real-time notifications are essential. The ability to establish event-based actions that automatically start whenever the algorithm detects a breach is crucial.

For instance, if there is a fire, sirens may ring throughout the structure, and the police may be contacted if there has been a break-in.

Without the need for human intervention, the owner, security personnel, and others will automatically receive an email or a notification.

These incredible AI-based video analytics tools can help you analyze media more effectively.

Rekognition by Amazon

A robust video analytics program with pre-trained and programmable computer vision APIs is called Amazon Rekognition. It performs facial recognition, object detection, and image analysis using deep learning technology.

Key Elements

• Rekognition moderation APIs should be integrated into social media and adverts to filter out objectionable and unsuitable content and produce a user-friendly, regulated medium.
• Utilize RekoRekognition's detection technology on photographs or videos to pinpoint features of the face like emotion, age, gender, and whether the eyes are open or closed.
• Utilize storage-based APIs to gather faces seen in a variety of photos or videos, then use the collection to search and match faces.
• It is practical for applications like document analysis and license plate identification to detect and extract text from photos and videos.
• Scenes like cars, houses, and landscapes are simple to recognize in photos and live video streaming as labels and scenes.

With the help of the Video Indexer, security and privacy are no longer myths. It has more than 3,500 security specialists committed to safeguarding your information and privacy. The platform is ideal for cutting-edge applications across numerous industries thanks to its cutting-edge certifications.

Clarifai

With the aid of computer vision and AI, Clarifai provides full motion video analysis. The tool has a tendency toward situation awareness and object detection, making it appropriate for security and surveillance operations.

Key Elements

• identifies particular behaviors or patterns of activity in the video that are being displayed in order to better understand how customers interact with items.
• Discover insights from unstructured data; identify anomalies in real-time to assist ISR military initiatives and enable quicker field choices.
• Improve response times, find individuals more quickly, and detect damage with AI combined with full motion video footage.
• Speech recognition and transcription software that can also recognise music and other sounds.

The greatest teams in the world, Canva, Nvidia, and other organizations rely on Clarifai for top-notch video analysis support. Additionally, when you sign up for Clarifai, you receive 1000 free operations per month.

Lumeo

With simple drag-and-drop tools and pre-built analytics building blocks, Lumeo Lumeo is a no-code custom video analytics platform that enables anyone to maximize the potential of video content.

Key Elements

• Lumeo can be used for a range of use cases without having to lift a finger because it has hundreds of ready-to-use AI models, tools, and connectors.
• Easy plug-and-play functionality allows for seamless integration of the program with current camera and video management systems.
• You may quickly create unique connections thanks to the full set of REST APIs and configurable Python nodes.
• Developers, solution engineers, and implementation teams have a built-in collaboration feature to offer solutions more quickly.

An all-in-one platform for video analytics is called Lumeo. Anyone may utilize cutting-edge analytics to the fullest extent without knowing any technical jargon thanks to its user-friendly design and ready-made AI models.

Applications of Tools for Video Analytics

As we previously stated, there are several use cases for video analytics technologies. To examine how video analytics are used in three important sectors—healthcare, security, and retail—we will limit our analysis to these three.

Healthcare

A smartphone app created by the University at Buffalo can assist identify childhood cases of autism spectrum disorder (ASD). The foundation of video analytics, motion detection, underlies how the app functions.

The software uses the camera on a smartphone to monitor a child's facial expression and eye movement as they see images of social settings (with numerous individuals).

Since children with ASD have different eye movements from those of people without autism, the app that tracks eye movements can identify them with accuracy.

Retail

Customers may check out of Amazon Go, a first-of-its-kind food shop, without having to wait in lengthy checkout lines. Customers are automatically charged for whatever they take from the shelf in order to accomplish this.

According to Amazon, each item a buyer selects from a shelf is immediately put to their online account's shopping basket. Amazon removes an item from a customer's virtual shopping cart when they put it back on the shelf. 

Amazon doesn't disclose much about the technology it uses, but it does say that it uses sophisticated computer vision and machine learning models along with a number of store-based sensors to make decisions with confidence over how much to charge customers for their purchases.

Security

An American citizen can be recorded on video more than 75 times per day, whereas a person in London is likely to be caught on a security camera over 300 times per day!

Therefore, it is impossible for humans to keep track of faces and deformities in densely populated areas. However, compared to human supervisors, video analytics systems may complete the task for you 10X more quickly and precisely.

No, we're not suggesting that you get rid of the security personnel you already have on duty, but these tools can help you execute your job more efficiently and successfully.

Final Reflections

Video analytics enabled by AI are no longer just "techie talk." In addition to other commercial functions, it has been employed in marketing, sales, and customer support. 

Video analytics are now more widely used across businesses thanks to their ability to save countless hours of labor and provide useful insights. We have attempted to cover all facet of AI-based video analytics in this paper.