<img src="https://ad.doubleclick.net/ddm/activity/src=10024890;type=invmedia;cat=front0;dc_lat=;dc_rdid=;tag_for_child_directed_treatment=;tfua=;npa=;ord=1?" width="1" height="1" alt=""> AI Auto-Tagging in Digital Asset Management
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Content Marketing Working with DAM

How to leverage AI for Digital Asset Management with Auto-Tagging

4. April 2024

Metadata is key for organizing your assets, ensuring accessibility, and creating automated content workflows to reduce manual work.

However, populating thousands of files with valuable and much-needed information or manually managing metadata after ingestion can be a tedious task – without the right tools. That’s where Artificial Intelligence (AI) for metadata tagging comes into play.

Fotoware Auto-Tagging with tags

What is Auto-Tagging?

Automated metadata tagging - or in short Auto-Tagging – is the process of automatically assigning descriptive metadata to large amounts of media files, such as photos, images, videos, or documents. Instead of manually tagging each asset with terms and phrases, Auto-Tagging utilizes algorithms and AI to analyze the content and generate relevant tags, keywords, asset-specific information, or descriptions. This process enriches your digital assets with valuable information that also is the basis for unlocking the full potential of your Digital Asset Management (DAM) system’s power.

What are tags and why do you need them?

In DAM, a metadata tag refers to a descriptive term or keyword assigned to an asset. Having meaningful tags helps organize and categorize your files and makes them significantly easier to find and work with.

AI autotagging with people detection, tags, and description

Auto-Tagging in Fotoware

The Fotoware DAM Auto-Tagging feature is provided by Computer Vision in Azure Cognitive Services and comes with various capabilities in facilitating the organization of your content with AI:

People Detection: Shows the number of people detected or the text ‘No people detected' if no people detected in the image.

Object Detection: Provides a tag for each object found in the image. For example, if an image contains a dog, a cat, and a car, the object detection operation will list these three.

Brand Detection: Returns the brand name if there are brand logos present in an image, based on a database of thousands of global logos to identify commercial brands.

Face Detection: Detects if there are human faces within an image and displays Yes or No.

Description: Returns a human-readable description based on different visual features.

Tags: Provides content tags for thousands of recognizable objects, living beings, scenery, and actions that appear in images.

Optical Character Recognition (OCR): allows you to extract printed or handwritten text from images, such as posters, street signs and product labels.


Use Cases for Auto-Tagging in DAM

The different capabilities of the AI-driven Auto-Tagging features can be used in a multitude of different ways.

Fotoware metadata: powerful search

Manage your asset collections

Create and manage collections of digital assets automatically in your DAM based on image contents! Metadata helps structuring and organizing assets by providing a framework for categorization and taxonomy. Assets can be grouped logically based on descriptive keywords or tags that represent their contents or themes, e.g. “nature”. This can for instance be a helpful tool when creating a marketing campaign with “nature” imagery.

GDPR consent status

Enhance Consent Management workflows for GDPR compliance

Is your organization concerned with privacy regulations and GDPR? Then Face Detection or People Detection can facilitate your Consent Management workflows! Use Auto-Tagging to automatically identify all photos that contain people (e.g. your employees) and request consent for the usage of their images for marketing purposes.

Learn More: Best Practices for GDPR Compliance when using images of employees

 

AI-driven text recognition

Are you working with archiving and categorization? Using AI for OCR can help you with the tedious task of digitalization! Text from photos of physical text documents can be automatically detected, extracted, and saved attached to the corresponding image. This way, users are able to search for text contents of images within their DAM.

Read More: Beyond digitization: How DAM helps Museums streamline operations

 

Multi-language collaboration

For companies operating in multiple countries or regions, employees, clients, and other DAM users may speak different languages. The Auto-Tagging feature supports metadata tagging in multiple languages, so users can search for assets using keywords in their preferred language. These capabilities improve findability of content significantly and facilitate effective collaboration across cultures and borders.

Fotoware AI autotagging benefits

The benefits of AI-powered Auto-Tagging

Implementing the Auto-Tagging feature to your DAM system comes with various benefits:

  • Boosting your company’s efficiency by saving time on manual metadata tagging
  • Enhancing search capabilities: More accurate keywords improve accessibility of your assets
  • Implement content workflows within the DAM: Metadata-driven workflows reduce the need for manual work and allow to process assets without human intervention
  • Improving collaboration: Rich metadata simplifies sharing assets internally or externally
  • Automatically detecting whether people are pictured in an asset to ensure GDPR compliance
  • Improve language availability thanks to accurate and consistent metadata enrichment

 

Read More: The top reasons why you should automate metadata tagging in your DAM

 

Ultimately, the Auto-Tagging functionality supports your organization’s competitive advantage and leads to tangible business results!

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