IEEE P3079.3/D03, May 2023

IEEE P3079.3/D03, May 2023 is a draft standard for a framework for evaluating the quality of digital humans, offering a structured way to assess how convincingly and consistently digital human representations perform. It is relevant where appearance, behavior, and interaction quality need to be judged against defined criteria. For teams working with synthetic characters, avatars, or other human-like digital models, IEEE P3079.3/D03, May 2023 can help support more repeatable evaluation and clearer comparisons.

IEEE P3079.3/D03, May 2023 overview

This draft standard focuses on evaluation methods for digital humans, with emphasis on building a framework rather than defining a single product requirement. In practice, that means it may help organize how quality is measured across visual realism, motion consistency, interaction behavior, and related factors. IEEE P3079.3/D03, May 2023 is useful for aligning technical teams around a common vocabulary and assessment approach when reviewing digital human systems for development, testing, or procurement.

Typical use cases

Typical use cases include assessing digital humans used in virtual assistants, training simulators, interactive media, and other applications where human-like behavior is important. The framework may support evaluation of character design, animation quality, responsiveness, and overall presentation in workflows that compare multiple implementations. IEEE P3079.3/D03, May 2023 can also be useful when teams need a consistent basis for reviewing prototype performance or documenting quality criteria for stakeholders.

Why this standard matters

This standard matters because digital human quality can be subjective without a clear evaluation framework. A structured approach helps reduce inconsistency in testing, improve design control, and make comparisons more defensible across versions or vendors. IEEE P3079.3/D03, May 2023 may also support procurement and acceptance reviews by giving organizations a more disciplined way to discuss performance, realism, and usability concerns before deployment.

• Framework for evaluating digital human quality
• Supports repeatable assessment criteria
• Relevant to avatars and human-like synthetic models
• Useful for testing, review, and comparison