AI Monitoring Camera Object Tracking via Characteristic Part Association
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Solution Overview
Problem
Existing monitoring camera systems struggle to achieve high accuracy in searching and tracking objects, such as people, within the angle of view due to reliance on face images alone, which is insufficient for precise identification and tracking.
Innovation Solution
The integration of artificial intelligence in monitoring cameras to detect and associate multiple characteristic parts of objects, such as whole body, scapula upper portion, and face, with a shared object ID, and to determine priority parts for tracking, enabling improved search and tracking accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If only face images are used for object identification and tracking, then the system complexity is low, but the search accuracy and identification precision are insufficient
Solution Approach 1:
The patent segments the object identification process into multiple characteristic parts (face, body, clothes, accessories) instead of relying on a single face image. Each part is detected and associated with the same object ID, enabling comprehensive tracking. This segmentation approach improves search accuracy by providing multiple identification features while managing complexity through modular AI processing.
2Measurement precision
If multiple characteristic parts are detected and associated with the same object ID, then the identification precision improves, but the processing time and computational load increase
Solution Approach 1:
The patent performs preliminary detection of multiple characteristic parts (face, body, clothes, accessories) and associates them with object IDs in advance. This preliminary action enables faster subsequent tracking and identification operations, as the system already has pre-processed information about multiple object parts. The AI processor efficiently manages this pre-processing to balance accuracy improvement with acceptable processing time.
3Reliability
If comprehensive object tracking is implemented using multiple characteristic parts, then the reliability of object identification improves, but the ease of operation and system simplicity decrease
Solution Approach 1:
The patent implements self-service through automatic AI-based detection and association of multiple characteristic parts. The system autonomously identifies objects, detects their characteristic parts, assigns object IDs, and performs tracking without manual intervention. This automation improves identification reliability while maintaining ease of operation, as users simply need to input search conditions without managing the complex detection and association processes.
Data Source
AI summary
A monitoring camera includes a capturing unit that is configured to capture an image of at least one object within the angle of view, and a processor that is equipped with the artificial intelligence and that is configured to detect a plurality of characteristic parts of the object reflected in a captured image input from the capturing unit based on the artificial intelligence. The processor associates, for each of the at least one object, information for specifying each of the plurality of detected characteristic parts with a same object ID.