Information Processing Apparatus for Crowd Congestion Detection
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Solution Overview
Problem
Existing video processing techniques for estimating crowd flow rates either impose a high processing load due to analyzing the entire image or fail to detect congestion in regions other than the set partial region, leading to potential missed detection of abnormal congestion states.
Innovation Solution
An information processing apparatus that determines the boundary between partial regions in an image and estimates movement information, prioritizing regions with a higher number of objects to detect congestion effectively while reducing processing load.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If statistical processing is performed on the entire image, then congestion detection coverage is improved, but processing load increases
Solution Approach 1:
The image is divided into multiple partial regions, and congestion estimation is performed separately for each region. This segmentation allows the system to maintain comprehensive monitoring coverage while reducing the processing load per region, as each region can be analyzed independently with fewer computational resources.
Solution Approach 2:
Instead of performing exhaustive statistical processing on the entire image, the system performs partial processing on selected partial regions. By focusing computational resources on specific regions of interest rather than the complete image, the system achieves effective congestion detection with reduced processing requirements.
2Device complexity
If a partial region of interest is set for flow rate estimation, then processing load is reduced, but congestion detection coverage in other regions is lost
Solution Approach 1:
The system processes multiple partial regions independently, with each region serving as a zone of interest. This multi-functional approach allows the same processing methodology to be applied across different regions, ensuring comprehensive congestion detection coverage while maintaining efficient processing loads through parallel independent analysis of each region.
3Measurement precision
If the number of objects in partial regions is used to determine boundaries, then congestion detection accuracy is improved, but additional processing steps are required
Solution Approach 1:
The system performs preliminary object detection and counting in partial regions before conducting flow rate estimation. By pre-identifying regions with a certain number of objects and using these object counts to determine boundaries for flow estimation, the system improves congestion detection accuracy while organizing processing steps in a logical sequence that minimizes redundant operations.
Data Source
AI summary
An information processing apparatus that detects an object from an image, includes a determination unit configured to determine a boundary at which a movement of the object between partial regions in the image is estimated, the partial regions each including a plurality of objects, and an estimation unit configured to estimate movement information indicating a number of objects that have passed the boundary determined by the determination unit.