How to unlock the power of AI facial recognition
| December 11, 2023
You likely use AI face recognition more often than you realize.
Searching for photos on your smartphone, social media tagging, and even your favorite virtual meeting’s blurred background all use AI face recognition.
But the best thing about AI facial recognition technology is its ability to help teams find and use content quickly.
You need AI tools to keep up with increasing content demands.
The entire content lifecycle, including creating, searching, editing, managing, and sharing, needs to be faster and more intuitive.
Yet the manual process of tagging and categorizing images is time consuming, and metadata must be added to content to be searchable…or does it?
Is metadata required to find content?
Not anymore.
AI can address the need to search, reuse, and repurpose images and videos.
Read on to learn what AI facial recognition is, how it works, and powerful use cases for your team in 2024.
What is AI face recognition?
AI face recognition identifies and verifies images containing people using machine learning and continuously improves accuracy by adapting to lighting, angles, and facial expressions.
Another important consideration is the difference between AI face detection and AI facial recognition.
Facial detection involves identifying and locating faces within an image or video in your system.
Facial recognition takes a leap forward, allowing you to identify faces but associate them with specific individuals. We’ll get into specific use cases shortly, but an example is finding images of your CEO for an upcoming marketing campaign within your system.
How does artificial intelligence facial recognition work?
Artificial intelligence facial recognition identifies specific individuals in images who have been detected inside platforms like digital asset management or video analysis software.
Teams can then leverage those images as part of their content programs. Let’s take a dive into how that works.
First, you need a data set. In the context of AI, that data typically includes a set of examples used to train, validate, and test within the AI tool. We can use marketing teams as an example. For marketers, the data set is usually marketing-related images and videos that have been used to train the AI model.
Once the data is loaded into an AI model, the technology works to better understand it. Faces are identified, recognized, and automatically labeled without the marketing team’s oversight. Now, anyone with access to the platform can find identified individuals for use in marketing collateral and other content programs.
Also, AI facial recognition only works for the specific tenant it’s added to in a system. In other words, when you’re searching for images of your CEO, nobody else can tap into your data, keeping your assets secure.
What are the advantages and disadvantages of AI facial recognition?
As with all great tools, AI facial recognition has advantages and disadvantages. We’ve covered some advantages already, like eliminating time-consuming “search and retrieval” missions for creative assets, but here are a few more to consider.
The five advantages of AI facial recognition.
- Efficient asset organization: AI automatically detects and tags images based on faces, reducing the time and effort required for manual organization. The time saved can used for high-impact work
- Easier content retrieval: Marketers and creatives can easily and quickly search for specific people, including well-known executives, models, or influencers
- Cross-departmental collaboration: A centralized digital asset management platform with AI facial recognition capabilities allows for sharing and collaboration on media files, reducing the need for frequent interdepartmental asset requests
- Simplified compliance: AI systems are designed with privacy-preserving features, and some are aligned with the principles of GDPR to support data security. As a result, images are approved, organized, and ready to share quickly in a compliant manner
- No need to reproduce missing content: When you can easily find content, it’s not misplaced or lost and then recreated — a frustrating and costly process
The three disadvantages of AI facial recognition.
- Privacy worries: A common worry about AI face recognition is privacy. Teams want to know: Can external parties see my data? And the answer is no. The technology only works once the face has been detected, recognized, and added to the database. And the data belongs to you, with zero external visibility
- Quality that varies by tool: The quality of AI face recognition tools can vary, so you’ll want to try different ones to ensure you select the best option
- Cost considerations: The cost of an AI face recognition tool also varies, so shop your options, test demos, and compare functionality and features to find the best tool that fits your budget
What are the AI tools that recognize faces?
Along with consumer-friendly and accessible platforms like Facebook, Apple Photos, and Google Photos, here are our favorite AI face recognition tools to consider as you expand your technology stack:
Valossa
Valossa is a video analysis platform that helps marketers understand important information about video content. It uses machine learning to recognize video topics, video tags, inappropriate content, and more.
Top features include:
- Content recognition: Tags important elements, such as objects, scenes, and people in video content
- Metadata enrichment: Automatically generates descriptive metadata to help with content organization
- Search and discovery: Includes advanced search capabilities to help with more efficient content retrieval
Valossa can also act as a personal editor, creating automated summaries of videos and generating various preview options for online distribution.
IBM Watson Visual Recognition
IBM Watson Visual Recognition uses AI and deep learning algorithms to analyze images and videos, providing useful insights for marketers.
Top features include:
- Audience insights: Provides marketers with insights into audience preferences and interactions with visual content
- Personalized advertising: Helps to create personalized ads tailored to the target audience
- Product recommendations: Analyzes visual data to provide product recommendations to users
Using IBM Watson Visual Recognition allows marketers to understand, personalize, and optimize their visual content strategies more effectively.
Canto
Canto’s digital asset management (DAM) platform helps to streamline content workflows by enabling teams to organize, find, and share digital assets from a single library.
Top features include:
- Organize and search: Powerful search and filtering alongside facial recognition powered by Amazon Rekognition help you easily locate content, including finding specific people, in your content library
- Plan, create, and collaborate: Canto helps marketers streamline creative processes with workflows, templates, and integrations to popular tools
- Share, publish, and control: Canto includes customizable and brandable sharing tools, access controls, and digital rights management
With AI facial recognition capabilities, Canto’s DAM helps teams to quickly tag, find, and access specific images across small and large content libraries.
Real-world use cases of AI-powered face recognition.
Curious to see if AI face recognition is a good fit for your content needs? Here are the most popular use cases of real-world AI facial recognition in action:
- Improving media organization: Streamline the management of content archives. For example, Meg of This Old House uses Canto’s DAM with AI-powered face recognition to retrieve specific images quickly and find content with specific team members and talent
- Locating influencer images: Your team might work with various influencers across campaigns. You can quickly organize influencer images based on AI face recognition to simplify content retrieval
- Improving campaign collaboration: Work with teams to leverage assets into new campaigns more effectively
- Event photography and recognition: Quickly identify event images, such as speakers, executives, and guests, to enhance post-event materials (and make next year’s event promotion so much easier)
How to select the most impactful AI facial recognition tool.
Once you understand what AI face recognition is, how it works, and its advantages and disadvantages, you might be ready for the next step — testing a few AI tools out. Here are three steps to select the right AI facial recognition tool:
1. Pinpoint your best use cases
What could help your team become more impactful? Maybe it’s spending less time searching for assets or meeting numerous interdepartmental collaboration requests. Start with the use case costing your team the most time and money.
2. Consider a DAM platform with built-in AI facial recognition capabilities
Consider a digital asset management (DAM) solution that helps you store, retrieve, and distribute digital assets like images and video content, helping you to manage large volumes of digital content more efficiently.
3. Evaluate integration capabilities
Whatever solution you pick, ensure it integrates with your favorite content creation, productivity, and collaboration tools to make your content programs run even more seamlessly.
Canto is a leader in digital asset management with AI and facial recognition.
As you explore possible uses of AI facial recognition and improve how you manage your digital content, you don’t need to go it alone. Canto is the leader in digital asset management and has AI facial recognition capabilities to make organizing, finding, and sharing your best content a cinch. It’s time to get control of your content library and power up your latest content programs.
Ready to learn the exact steps to unlock AI for your content programs? Check out our on-demand webinar on the Secrets to Creating an AI-Powered Content Strategy.