Azure AI Video Indexer terminology & concepts

Important

Due to the Azure Media Services retirement announcement, Azure AI Video Indexer announces Azure AI Video Indexer features adjustments. See Changes related to Azure Media Service (AMS) retirement to understand what this means for your Azure AI Video Indexer account. See the Preparing for AMS retirement: VI update and migration guide.

This article gives a brief overview of Azure AI Video Indexer terminology and concepts. Also, review transparency note overview

Artifact files

If you plan to download artifact files, beware of the following warning:

Warning

We do not recommend that you use data directly from the artifacts folder for production purposes. Artifacts are intermediate outputs of the indexing process. They are essentially raw outputs of the various AI engines that analyze the videos; the artifacts schema may change over time. It is recommended that you use the Get Video Index API, as described in Get insights and artifacts produced by the API.

Confidence scores

The confidence score indicates the confidence in an insight. It's a number between 0.0 and 1.0. The higher the score the greater the confidence in the answer. For example:

"transcript":[
{
  "id":1,
  "text":"Well, good morning everyone and welcome to",
  "confidence":0.8839,
  "speakerId":1,
  "language":"en-US",
  "instances":[
     {
	"adjustedStart":"0:00:10.21",
	"adjustedEnd":"0:00:12.81",
	"start":"0:00:10.21",
	"end":"0:00:12.81"
     }
  ]
},

Content moderation

Use textual and visual content moderation models to keep your users safe from inappropriate content and validate that the content you publish matches your organization's values. You can automatically block certain videos or alert your users about the content. For more information, see Insights: visual and textual content moderation.

Insights

Insights contain an aggregated view of the data: faces, topics, text-based emotion detection. Azure AI Video Indexer analyzes the video and audio content by running 30+ AI models, generating rich insights.

For detailed explanation of insights, see Azure AI Video Indexer insights.

Keyframes

Azure AI Video Indexer selects the frame(s) that best represent each shot. Keyframes are the representative frames selected from the entire video based on aesthetic properties (for example, contrast and stableness). For more information, see Scenes, shots, and keyframes.

Time range vs. adjusted time range

Time range is the time period in the original video. Adjusted time range is the time range relative to the current playlist. Since you can create a playlist from different lines of different videos, you can take a one-hour video and use just one line from it, for example, 10:00-10:15. In that case, you'll have a playlist with one line, where the time range is 10:00-10:15 but the adjusted time range is 00:00-00:15.

Widgets

Azure AI Video Indexer supports embedding widgets in your apps. For more information, see Embed Azure AI Video Indexer widgets in your apps.