Person Detection Using Weather-Adaptive Umbrella Recognition Models
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Solution Overview
Problem
Existing person detection systems using pattern recognition struggle with reliability when individuals use weather protectors like umbrellas, as the hidden body parts cause mismatches in image recognition, reducing detection accuracy.
Innovation Solution
A person detection apparatus that incorporates a weather determination section and a storage portion with specific recognition models for individuals using umbrellas, adjusting recognition scores based on weather conditions to improve detection accuracy by considering the influence of umbrella usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional pattern recognition using standard recognition models is used, then detection speed and simplicity are maintained, but detection reliability deteriorates when persons use weather protectors like umbrellas
Solution Approach 1:
The system performs preliminary weather condition determination before pattern recognition, and pre-stores multiple recognition models corresponding to different weather conditions. This allows the system to select the appropriate recognition model in advance, improving detection reliability when persons use weather protectors without significantly increasing system complexity
Solution Approach 2:
The system dynamically selects recognition models based on determined weather conditions. The person recognition section switches between different recognition models (e.g., umbrella-hold model vs. standard model) according to the current weather condition, enabling adaptive detection that maintains high reliability across varying environmental conditions
2Measurement precision
If the recognition model is adjusted to account for umbrellas, then detection accuracy for persons with umbrellas improves, but detection accuracy for persons without umbrellas may deteriorate
Solution Approach 1:
The system applies different recognition models to different weather conditions rather than using a single universal model. The umbrella-hold recognition model is specifically applied when weather conditions indicate high probability of umbrella usage, while standard recognition models are used otherwise, ensuring optimal detection accuracy for each specific condition
Solution Approach 2:
The system changes the recognition model parameter based on weather condition determination. By switching between different recognition models (different parameter sets) according to weather conditions, the system maintains high detection accuracy for both persons with and without umbrellas, avoiding the trade-off between specialized and general detection
3Reliability
If weather condition information is integrated into pattern recognition, then recognition ratio for persons with protectors improves, but computational complexity increases
Solution Approach 1:
The weather determination section performs weather condition analysis before the pattern recognition process, and the person recognition section selects the appropriate pre-stored recognition model based on this determination. This preliminary classification approach avoids complex real-time adjustments during recognition, improving recognition ratio for persons with protectors while controlling computational complexity
Solution Approach 2:
The system stores multiple copies of recognition models (umbrella-hold model, standard model) in the storage portion, each optimized for different weather conditions. This allows the system to simply select and use the appropriate model copy based on weather conditions, improving recognition accuracy without requiring complex computational adjustments during the recognition process
Data Source
AI summary
A person detection apparatus determines a weather condition such as rain and solar radiation based on a variety of information from a weather information input portion. Then, based on a determination result of the weather condition, the umbrella ratio showing the ratio of persons with umbrellas is calculated. The person detection apparatus uses a no-umbrella recognition model describing a person with no umbrella and an umbrella-hold recognition model describing a person with umbrella in order to perform pattern recognition to an input image to derive recognition scores based on the respective recognition models. Then, the umbrella ratio depending on the weather condition is used to correct the respective recognition scores based on the pattern recognition using the no-umbrella model and the recognition score based on the pattern recognition using the umbrella-hold model; the corrected recognition scores are output as a final detection result.