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VULTUROIDS | AI Video Continuity & Identity Testing
How well can an AI video model transform a complex cinematic reference image into motion without compromising visual identity, world-building or scene continuity?
Through Teamworks Creative, I conducted an experimental generative filmmaking study for VULTUROIDS, a dark, post-apocalyptic political-fantasy concept.
The creative challenge
The scene depicts a ruined United Nations headquarters in a fictional future, surrounded by a vast assembly of vulture-like figures, imposing banners and a central winged character.
The objective was to evaluate whether image-to-video generation could preserve this complex visual world while introducing convincing cinematic movement.
Production and testing workflow
• Developed cinematic 9:16 reference-image variations using Dreamina AI.
• Explored architectural composition, lighting, crowd arrangement and character positioning.
• Tested an image-to-video sequence using Kling 3.0 Standard through Creen AI.
• Reviewed the generated footage for movement, identity consistency, scene preservation and unintended visual changes.
Key observations
What worked: The video demonstrated promising atmosphere and crowd movement, showing how generative video can bring scale and energy to an established visual concept.
What required improvement: Prominent character identities and visual details were not consistently maintained. This made the result useful as research evidence rather than approved final-production footage.
What I evaluated
• Reference-image fidelity
• Character and crowd identity consistency
• Environment and architectural continuity
• Movement and cinematic atmosphere
• Unintended visual changes
• Suitability for further production development
Key finding
A visually impressive AI-generated sequence is not necessarily production-ready. Large-scale motion and atmosphere can succeed while character identity and continuity still require revision.
Project: VULTUROIDS — Generative Film R&D
Production: Teamworks Creative
Role: AI Creative Direction, Prompt Development & Visual Quality Evaluation
Tools and models: Dreamina AI for reference imagery; Kling 3.0 Standard via Creen AI for video testing.
Supporting reference images, source-prompt evidence, the generated clip and QA notes are provided in the project folder.
Research disclosure: The Dreamina reference-image prompt is evidenced by platform screenshots. The complete original Kling video-generation prompt has not been independently recovered.
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