Image Object Counting via Trajectory Line Intersection
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Solution Overview
Problem
Existing image-based object counting methods require extensive calculations to determine whether an object has crossed a boundary, as they often compare pixel values across the entire image, leading to inefficiencies in processing and accuracy.
Innovation Solution
The method involves rasterizing a counting line into pixels, determining corresponding pixels on a trajectory line, and assessing intersection by comparing coordinate values, reducing calculations by classifying pixels into sections and determining intersection direction, thereby efficiently counting objects that pass the counting line.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If pixel values across the entire image are compared to determine object crossing, then object counting accuracy is maintained, but computational complexity and processing time increase significantly
Solution Approach 1:
The image is segmented by introducing a counting line that divides the space into two regions. Instead of comparing all pixel values across the entire image, the method only needs to track trajectory lines intersecting with the counting line, significantly reducing the computational scope while maintaining accurate object crossing detection
Solution Approach 2:
The method extracts only the essential information needed for object counting by focusing on trajectory lines and their intersection points with the counting line. This extraction approach eliminates unnecessary pixel comparisons across the entire image, reducing computational complexity while preserving counting accuracy
2Reliability
If extensive pixel comparisons are performed across the entire image, then comprehensive object detection is achieved, but processing time increases
Solution Approach 1:
The method performs preliminary action by pre-defining trajectory lines based on object movement patterns before conducting the actual counting. This allows the system to focus computational resources only on relevant trajectory segments that may intersect with the counting line, rather than processing all pixels in the image
Solution Approach 2:
By segmenting the problem into trajectory line detection and intersection determination, the method processes only the necessary portions of the image data. This segmentation enables comprehensive object detection while minimizing processing time by avoiding unnecessary pixel comparisons
3Productivity
If coordinate value comparisons of two points on trajectory line are used to determine intersection, then computational requirements are reduced, but implementation complexity increases
Solution Approach 1:
The method changes the parameters being compared from full pixel values across the entire image to specific coordinate values of only two points on each trajectory line. This parameter change dramatically reduces computational requirements while the intersection determination logic, though mathematically sophisticated, can be efficiently implemented through standardized algorithms
Data Source
AI summary
An image-based object counting method includes rasterizing a counting line in an image into counting line pixels; determining two points on a trajectory line included in the image, as target pixels; determining, from the counting line pixels, corresponding pixels that corresponds to the target pixels; determining whether the counting line intersects with the trajectory line based on the target pixels and the corresponding pixels; and determining the number of one or more trajectory lines including the trajectory line that intersect with the counting line as the number of objects that pass through the counting line.