Mastering AI Video Scene Prompts: Camera Lenses, Lighting & Motion Cues

## Why Generic Prompts Fail in AI Video Generation When you type `"a car driving down a futuristic city road"` into an AI video generator, you often get a video where the car morphs into the road, the wheels spin backwards, or the camera drifts erratically. Generative video models require **Cinematographic Precision**—explicit parameters for focal length, camera movement, light sources, and particle motion. ### The 4 Pillars of a Cinematic AI Video Prompt #### Pillar 1: Camera Framing and Lens Specification Always specify the focal lens and camera body aesthetic: - **35mm Anamorphic**: Creates widescreen cinematic bokeh and horizontal blue lens flares. - **85mm Portrait Prime (f/1.4)**: Ultra-shallow depth of field, keeping the subject crisp while blurring the background. - **Drone FPV Top-Down**: High speed, dynamic altitude descent. #### Pillar 2: Explicit Motion Action Avoid passive nouns. Describe the exact vector of movement: - *Bad*: "A girl standing in the rain." - *Good*: "Slow motion 60fps tracking shot. Water droplets bounce off an iridescent umbrella as she walks towards camera right." #### Pillar 3: Lighting and Atmospheric Density AI diffusion models build realism through lighting interaction: - **Golden Hour Volumetric Rays**: Natural warmth with soft backlighting. - **Chiaroscuro / Neo-Noir**: High contrast shadow gradients with single key light source. - **Cyberpunk Rim Light**: Vibrant magenta and cyan dual-tone edge lighting. #### Pillar 4: The Clean Starting Frame Strategy For the highest fidelity in Runway or Kling, first generate an ultra-high resolution still frame using Midjourney with `--ar 16:9 --style raw`, then use image-to-video with motion prompting. Explore our free **Video Scene Prompt Generator** to automatically synthesize Hollywood-grade lighting, camera, and motion commands for your next creative project.