AI Scene Detection
AI 智能场景识别
Hybrid ML + histogram analysis for intelligent exposure recommendations
Reflected light meters – including the ones built into film cameras – are calibrated to assume the scene averages to 18% gray. This assumption fails in many real-world situations: a snow-covered landscape reads as overexposed, a backlit portrait underexposes the face, and a night cityscape confuses the meter entirely. FilmMeter’s AI scene detection solves this problem by identifying the type of scene you are shooting and recommending exposure compensation before you take the shot.
Two-Phase Hybrid Detection
FilmMeter uses a sophisticated two-phase approach that balances speed with accuracy:
Phase 1 – Histogram Analysis (Fast): Every frame is analyzed for luminance distribution, reflectance characteristics, and contrast ratios. This fast analysis runs continuously and identifies basic exposure challenges like high-key scenes, low-key scenes, and extreme contrast situations. The histogram analyzer detects when the scene’s average reflectance deviates significantly from 18% gray and suggests initial EV compensation.
Phase 2 – Places365 ML Classification (Intelligent): When additional context would improve the recommendation, FilmMeter’s custom-trained CoreML model classifies the scene using a neural network trained on the Places365 dataset. This identifies specific scene types – ski slopes, beaches, concert stages, sunsets, forests, indoor interiors – and applies scene-specific compensation rules refined through extensive real-world testing with film.
Scene Types and Compensation Values
The detection system recognizes dozens of scene categories and maps them to appropriate EV adjustments:
- Snow and beach scenes: +1.0 to +1.5 EV to prevent underexposure of bright, reflective surfaces
- Backlit subjects: +1.0 to +2.0 EV to preserve subject detail against bright backgrounds
- Night and low-light scenes: Variable compensation based on highlight-to-shadow ratio
- Stage and concert lighting: Spot-weighted adjustments for high-contrast performance environments
- Portraits in open shade: Subtle +0.5 EV for pleasing skin tone exposure on color negative film
- Dark forests and interiors: +0.5 to +1.0 EV to open up shadow detail
Fully Offline and Private
All scene detection runs entirely on-device using Apple’s CoreML framework. No images are uploaded to any server, no internet connection is required, and no scene data leaves your iPhone. The ML model is embedded in the app bundle and optimized for real-time inference on the Neural Engine. This means the feature works just as well in a remote mountain location with no cell service as it does in a studio with gigabit internet.
Integration with Light Metering
Scene detection works hand-in-hand with precision light metering – the AI recommendations appear as suggested EV offsets that you can accept, modify, or ignore. This preserves your creative control while providing an intelligent safety net against common metering pitfalls. The system is especially valuable when shooting slide films like Fuji Velvia or Provia where even half a stop of exposure error can ruin a frame. Combined with film roll management, your accepted compensation values are recorded in your shooting log for post-processing reference.