Event Tagging System for Multi-Object Situation Perception
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Solution Overview
Problem
Existing technologies are unable to effectively perceive complex situations by detecting and tracking multiple objects using camera video, limiting their ability to apply appropriate actions in response to various events.
Innovation Solution
A system and method for perceiving event tagging-based situations that utilize an object detection unit, an object tracking unit, an event tagging unit, and an action generation unit to detect objects, track their movement, sense predefined events, and generate appropriate actions based on event combinations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If object detection and tracking functions are applied to camera video to perceive situations, then the ability to detect and track multiple objects is improved, but the complexity of the system increases
Solution Approach 1:
The system segments the situation perception process into distinct functional modules: object detection unit, object tracking unit, event tagging unit, and action generation unit. Each unit handles a specific aspect of the processing pipeline, from detecting objects in video frames to tracking their movement and generating actions based on event combinations. This modular segmentation reduces system complexity by making each component independent and manageable.
Solution Approach 2:
The event tagging unit serves as an intermediary between object tracking and action generation. It receives location information from the tracking unit, tags events based on predesignated conditions, and passes structured event information to the action generation unit. This intermediary layer simplifies the overall system by providing a standardized interface and buffer between the tracking and decision-making components.
2Adaptability or versatility
If event tagging and action generation functions are added to perceive complex situations, then the versatility of situation perception is improved, but the device complexity increases
Solution Approach 1:
The system dynamically generates actions based on combinations of tagged events rather than using fixed predetermined responses. The action generation unit receives event tag lists from the event tagging unit and creates context-appropriate actions based on the specific combination of events detected. This dynamic approach enhances versatility while keeping the system structure relatively simple by using rule-based generation rather than complex decision trees.
Solution Approach 2:
The system performs preliminary event tagging during the tracking phase, preparing structured event information before action generation is needed. By pre-tagging events as objects move through designated areas and perform predesignated actions, the system reduces the computational burden during the final action generation stage, allowing for more versatile situation perception without proportionally increasing real-time processing complexity.
3Quantity of substance
If multiple objects are detected and tracked to perceive various situations, then the quantity of detectable objects is improved, but the difficulty of detecting and measuring increases
Solution Approach 1:
The system creates simplified copies of object information in the form of event tag lists that capture essential movement patterns and events. Instead of processing complete tracking data for multiple objects simultaneously, the system generates condensed event representations that preserve the necessary information for situation perception while reducing measurement and analysis complexity. Each object's trajectory is copied into discrete event tags that are easier to process.
Data Source
AI summary
The present invention relates to a method for perceiving an event tagging-based situation and a system for same which recognize a plurality of objects by using camera images and apply technology for tracking the movements of the plurality of recognized objects to enable the perception of various situations.