Pedestrian Headcount Tracking via Foreground-Model Matching
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Solution Overview
Problem
Existing headcount counting systems face inaccuracies due to pedestrians walking side by side and occlusion of objects, which affect the efficiency and accuracy of counting.
Innovation Solution
A method and apparatus that set object models and a detection line in surveillance video frames, extract and process foreground images to eliminate interference, match moving objects with object models, and track characteristics to accurately count pedestrians, thereby addressing the issues of side-by-side walking and occlusion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional headcount counting methods are used, then the system can count pedestrians, but the accuracy deteriorates when pedestrians walk side by side or objects occlude each other
Solution Approach 1:
The patent segments the headcount counting process into distinct phases: background modeling to separate foreground pedestrians, individual pedestrian detection, and tracking. By dividing the complex counting task into manageable segments, the system can accurately count pedestrians even when they walk side by side or occlude each other, directly resolving the accuracy-reliability contradiction.
Solution Approach 2:
The patent applies preliminary action by first establishing a background model before counting begins. This pre-processing step creates a reference framework that enables accurate detection of foreground pedestrians in subsequent frames, ensuring high accuracy from the start and maintaining reliability throughout the counting process in complex scenarios.
2Ease of operation
If simple counting methods are used, then the system is easy to operate, but the efficiency deteriorates due to inaccuracies requiring manual verification
Solution Approach 1:
The patent implements feedback mechanisms where the system continuously monitors counting results and adjusts its detection and tracking parameters accordingly. This automated feedback loop maintains high accuracy without requiring manual intervention, thereby preserving both ease of operation and counting efficiency, resolving the contradiction between operational simplicity and productivity.
Data Source
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AI summary
A method, apparatus and system for acquiring headcount are provided. Data frames are acquired from a surveillance video, object models are set in the data frames, and a foreground image is extracted from the data frames, wherein the foreground image includes moving objects extracted from the data frames; the moving objects in the foreground image is matched with the object models, the headcount in corresponding data frames is acquired according to a result of the matching, characteristics of the matched moving objects are extracted, and the corresponding moving objects are tracked based on the characteristics; the actual headcount for a predetermined time segment of the surveillance video is acquired based on a result of the tracking and the acquired headcount for each of the data frames, wherein the result of the tracking includes: an indication of whether some or all of the data frames includes a same moving object.