Vehicle Occupant Counting via Multi-View Coordinate Grouping
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing methods for detecting the number of persons on a vehicle are inaccurate due to variations in seating layouts and reliance on pre-held information about seating arrangements, which can lead to insufficient accuracy in counting occupants.
Innovation Solution
An analysis apparatus that continuously images a vehicle from different directions, detects predetermined vehicle parts and human faces, assigns coordinates in a vehicle coordinate system, groups faces with similar coordinates, and counts these groups to determine the number of persons, eliminating the need to identify specific seats.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If pre-held seating layout information is used to detect persons, then detection process is simplified, but detection accuracy deteriorates due to variations in actual seating arrangements
Solution Approach 1:
The invention extracts only the necessary information (coordinates of detected persons) from multiple images without requiring pre-held seating layout information. By taking out the dependency on predetermined seating arrangements, the system achieves both simplified operation and improved accuracy through coordinate-based grouping of detected persons across multiple images.
2Measurement precision
If multiple images are continuously captured to improve detection accuracy, then person counting precision improves, but processing time and system complexity increase
Solution Approach 1:
The system performs preliminary detection of person coordinates in multiple continuously captured images before final counting. By detecting coordinates in advance across multiple images and then grouping them, the system prepares data structure beforehand, which streamlines the final counting process and reduces overall processing time while maintaining high accuracy.
Solution Approach 2:
The invention uses coordinate information as a simplified copy or representation of person positions instead of processing entire images for counting. By working with coordinate data rather than full image processing, the system significantly reduces computational complexity and processing time while preserving detection accuracy through coordinate-based grouping.
3Measurement precision
If coordinate-based grouping method is used instead of seat identification, then detection accuracy improves by avoiding seating layout assumptions, but coordinate system establishment complexity increases
Solution Approach 1:
The coordinate system established in the invention serves multiple functions: it provides a reference framework for detecting person positions, enables grouping of detected persons across different images, and eliminates dependency on specific seating layout information. This universal coordinate-based approach works for various vehicle types and seating arrangements, achieving high detection accuracy without requiring complex seat identification mechanisms.
Data Source
Figure 1
Figure 2
Figure 3
AI summary
According to the present invention, there is provided an analysis apparatus (10) including an image analysis unit (11) that detects a predetermined part of a vehicle and persons on the vehicle from each of a plurality of images obtained by imaging the same vehicle from different directions a plurality of times, and detects coordinates of each of the plurality of persons in a coordinate system having the detected predetermined part as a reference; a grouping unit (12) that groups the persons detected from the different images, on the basis of the coordinates; and a counting unit (13) that counts the number of groups.