Background
Target detection in complex scenes often faces challenges such as occlusion and similar object interference, which affects detection accuracy.
prescription
- Utilizing advanced reasoning skills: the tool is able to understand scene contextualization and automatically handle occlusion, etc.
- Optimize prompting strategy::
- For multi-object scenarios, use hierarchical cues (e.g., "Detect all vehicles", then "Detect blue vehicles").
- Add descriptive qualifiers for objects with fuzzy boundaries (e.g. "partially obscured bicycle")
- Multiple testing and validation: For important scenarios, different cues can be used for cross-validation
operation suggestion
- For congested scenarios, a whole-to-local detection strategy is suggested
- Cue detection at different angles for the same scene if necessary
- Make the most of the 20-30 seconds of analysis time to allow the AI to reason fully
Effectiveness evaluation
With a reasonable prompting strategy, the detection accuracy of complex scenes can be significantly improved while maintaining a processing speed of 20-30 seconds.
This answer comes from the articleAgentic Object Detection: A Visual Object Detection Tool without Annotation and TrainingThe
May not be reproduced without permission:AI productivity tools " How to improve the accuracy of target detection in complex scenes?
