Crowd Estimation System with Dynamic Technique Switching
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Solution Overview
Problem
Existing crowd estimation techniques are not suitable for all environmental and crowd conditions, leading to reduced accuracy due to occlusions and varying crowd densities.
Innovation Solution
A method and system that integrate multiple crowd estimation techniques, allowing for automatic switching between them based on real-time performance modeling and crowd level estimation, to provide improved accuracy across various conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If background subtraction techniques are used for crowd estimation, then the technique is simple to implement, but accuracy deteriorates when there is overlap of humans (occlusion)
Solution Approach 1:
The patent combines multiple crowd estimation techniques (background subtraction, body part recognition, combined head pattern techniques) into a unified system that leverages the strengths of each method while compensating for their individual weaknesses, particularly addressing occlusion issues by integrating techniques that perform well under different conditions
2Reliability
If body part recognition techniques are used for crowd estimation, then the technique can handle certain crowd conditions, but accuracy deteriorates in cases of occlusions at high crowd densities
Solution Approach 1:
The system dynamically changes operational parameters by selecting different estimation techniques based on detected crowd conditions such as density levels and occlusion patterns, switching from body part recognition to combined head pattern techniques when occlusions are detected at high densities
3Measurement precision
If combined head pattern techniques are used for crowd estimation, then accuracy is improved at high crowd densities, but accuracy deteriorates at sparse crowd levels or low crowd densities
Solution Approach 1:
The patent implements a dynamic technique selection mechanism that adapts the crowd estimation approach based on real-time analysis of crowd density and spatial distribution, switching between combined head pattern techniques for high density scenarios and other methods for sparse crowd levels to maintain optimal accuracy across varying conditions
4Ease of operation
If a single crowd estimation technique is used, then the system is simple to operate, but accuracy deteriorates across varying environmental and crowd conditions
Solution Approach 1:
The patent creates a universal crowd estimation system that integrates multiple estimation techniques into a single multi-functional platform, automatically selecting the appropriate technique based on environmental conditions and crowd characteristics, thereby maintaining both operational simplicity and high accuracy across diverse scenarios
Data Source
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AI summary
Methods and systems for crowd level estimation are provided. The system includes a plurality of performance modeling modules (206), an input module (202) and a crowd estimation technique integration module. The plurality of performance modeling modules (206) performance model each of a plurality of crowd estimation techniques based on an accuracy thereof at different crowd levels and/or at different locations. The input module (202) receives an image of a crowd. The crowd estimation technique integration module (208) selects one or more of the plurality of crowd estimation techniques in response to the performance modeling of the one or more of the plurality of crowd estimation techniques and an estimated crowd level and/or an estimated location. The crowd estimation technique integration module (208) then estimates a crowd count of the crowd in the received image in accordance with the selected one or more of the plurality of crowd estimation techniques.