Object Tracking via Classification-Based Processing Resource Allocation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing object tracking systems face challenges in managing a large number of tracks in a three-dimensional space, particularly when the number of objects exceeds the processing capability of the system.
Innovation Solution
The system classifies tracks and adjusts processing accordingly, prioritizing confirmed tracks and limiting processing for detections that do not conform to known tracks, thereby optimizing resource allocation and increasing accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the system processes all detections equally, then comprehensive tracking coverage is maintained, but processing resources are overwhelmed when the number of objects exceeds system capability
Solution Approach 1:
The patent applies different processing quality levels to different tracks based on their classification status. Confirmed tracks receive full processing with rigorous validation, while unconfirmed tracks receive limited processing with simplified validation. This local differentiation of processing quality allows the system to maintain high accuracy for reliable tracks while conserving resources on uncertain detections.
Solution Approach 2:
The patent segments the tracking system into distinct processing paths based on track classification. There is a confirmed track processing path with full validation and an unconfirmed track processing path with limited validation. This segmentation allows the system to handle different types of tracks with appropriate resource allocation, resolving the contradiction between comprehensive processing and resource constraints.
2Measurement precision
If the system applies full processing to all tracks, then tracking accuracy is maximized, but system efficiency decreases due to unnecessary processing of unconfirmed detections
Solution Approach 1:
The patent applies partial processing to unconfirmed tracks by performing only limited validation checks rather than full processing. This partial action is sufficient to maintain basic tracking functionality for uncertain detections while avoiding the time cost of complete validation. Full processing is reserved only for confirmed tracks where high accuracy is essential.
Solution Approach 2:
Different processing depths are applied locally to different tracks based on their confirmation status. Confirmed tracks receive deep processing with comprehensive validation to ensure maximum accuracy, while unconfirmed tracks receive shallow processing with minimal validation. This local quality differentiation optimizes the balance between accuracy and processing time.
3Loss of information
If the system processes every detection with equal detail, then no tracking information is lost, but resource allocation becomes inefficient when many detections do not conform to known tracks
Solution Approach 1:
The patent extracts and separates the validation step from the main processing flow for unconfirmed tracks. By taking out the full validation process and replacing it with a simplified check, the system maintains essential tracking information while eliminating excessive resource consumption. Only confirmed tracks undergo the complete validation sequence that ensures information completeness.
Solution Approach 2:
The system changes the processing parameter (validation depth) based on track classification. For unconfirmed tracks, the validation parameter is reduced to a minimal check that preserves basic tracking information. For confirmed tracks, the validation parameter is set to full processing that ensures complete information accuracy. This dynamic parameter adjustment resolves the resource allocation inefficiency.
Data Source
AI summary
In various example embodiments, a system and method for tracking objects in a three-dimensional space is disclosed. One method includes receiving detections representing targets, increasing a classification of a track in response to a detection matching the track, decreasing a classification of a track in response to no detections matching the track, and processing detections according to a classification level of the track.