1. Why are photos the primary output?
Bridge defect recognition (especially cracks) requires static high-resolution imagery. A single 100MP photo reaches 40-50 megabytes and fully preserves fine defect detail, supporting pixel-level mapping onto the 3D model; video streams lack sufficient clarity and single-frame detail, and are mainly used for route confirmation and playback. Defect detection and measurement are based on photo data.
2. Division of labor between photos and video
| Purpose | Collection method | Description |
|---|---|---|
| Defect detection and measurement | HD photos | Basis for AI detection and 3D mapping |
| Route confirmation and playback | Video | Supports operation management and demos |
| Expressway pavement inspection | High-speed camera burst | Clear imaging at 60-80 km/h |
3. How does the data flow?
After capture, photos are uploaded to the platform, screened and detected by AI, then manually re-verified and mapped onto the 3D model, forming a complete inspection workflow.
4. Applicable conditions and scenarios
- Bridge inspection mainly collects photos; AI detection is based on photo data
- Dynamic imagery needs (e.g. route display) are supplemented with video
- Data is processed and analyzed uniformly on the platform after upload
5. Notes
Video serves as supporting evidence and demo material but does not replace photos for defect rating and measurement; report output is based on high-definition photos.