Pedestrian Traffic Counting Using Body-Derived Head Detection
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Solution Overview
Problem
Existing image recognition-based pedestrian traffic statistics are prone to low accuracy due to issues such as missed detection caused by light or environment and false detection from body box jitter.
Innovation Solution
Perform body detection to obtain body detection boxes, determine head detection boxes through zoom-out operations based on body detection box dimensions and human body posture, and use these pseudo head detection boxes to calculate traffic statistics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If face detection is used for traffic statistics, then the method is simple to implement, but detection accuracy decreases due to missed detection caused by light or environment
Solution Approach 1:
The patent introduces body detection boxes as an intermediary to derive head detection boxes. Instead of directly detecting faces which are sensitive to lighting and environment, the system first detects body boxes (which are more robust) and then calculates head boxes through zoom-out operations. This intermediary approach maintains implementation simplicity while significantly improving detection accuracy in various environmental conditions.
2Reliability
If body detection is used for traffic statistics, then detection robustness improves, but false detection increases due to body box jitter
Solution Approach 1:
The patent extracts the head region from the body detection box through zoom-out operations. By focusing only on the head area (a subset of the body box) rather than the entire body box, the system eliminates false detections caused by body jitter while maintaining the robustness of body detection. The head region is less susceptible to movement-induced jitter compared to the full body box.
3Measurement precision
If head detection is performed directly, then traffic statistics accuracy improves, but detection reliability decreases due to missed detection in adverse conditions
Solution Approach 1:
The patent performs body detection as a preliminary action before deriving head detection boxes. Body detection is performed first under various environmental conditions to establish a reliable baseline, and then head boxes are calculated from these body boxes. This preliminary body detection step ensures that even in adverse conditions, a reliable detection foundation exists before extracting head regions, thereby maintaining both accuracy and reliability.
Data Source
AI summary
The present disclosure provides a traffic statistics collection method and apparatus. The method includes: obtaining a first image of a target place; performing body detection on the first image to obtain body detection boxes of respective target objects in the first image, where the body detection boxes indicate body areas of the respective target objects; for each target object of the respective target objects, determining a head detection box of the target object according to the body detection box of the target object, wherein the head detection box indicates a head area of the target object; and obtaining a traffic statistics result of the target place according to head detection boxes of the respective target objects.