Object Recognition Identity Association Tracking
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Solution Overview
Problem
Existing systems for facial recognition in security monitoring lose individual identity when the person moves out of the monitored area, requiring re-identification upon re-entry, and often require a clear view of the face for accurate recognition.
Innovation Solution
A method and system for object recognition and association with identity, using multiple image capture devices and a backend processing system to associate physical characteristics and objects with individuals, assigning unique identifiers based on confidence thresholds, and enabling identification even when facial features are not visible by utilizing beacons and object recognition.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If facial recognition is used to identify individuals, then identification accuracy is improved, but the system fails when the individual moves outside the monitored area or when facial view is not clear
Solution Approach 1:
The system segments the identification process into multiple components: facial recognition for initial identification, physical characteristic extraction for intermediate tracking, and object association for continuous identification. This segmentation allows the system to use different identification methods depending on the situation, maintaining both accuracy and continuity.
Solution Approach 2:
The system implements multi-functionality by enabling the same monitoring system to perform multiple identification tasks: facial recognition when the face is visible, physical characteristic recognition when facial view is limited, and object-based identification when the individual is outside the monitored area. This universal approach resolves the contradiction between accuracy and continuity.
2Adaptability or versatility
If multiple image capture devices are deployed to maintain continuous tracking, then tracking continuity is improved, but system complexity increases
Solution Approach 1:
The system merges data from multiple image capture devices with data from beacons and object recognition systems into a unified identification framework. By combining these different data sources and processing them through a single backend system with centralized database, the system achieves continuous tracking without proportionally increasing overall system complexity.
Solution Approach 2:
The backend system acts as an intermediary that receives data from multiple image capture devices, beacons, and object recognition systems, processes this information, and produces unified identification results. This intermediary approach allows multiple devices to work together seamlessly without each device needing complex direct communication with every other device, thereby managing system complexity.
3Measurement precision
If re-identification is required when individuals re-enter the monitored area, then identification accuracy can be maintained, but time loss occurs
Solution Approach 1:
The system performs preliminary action by maintaining a database of identified individuals and their associated physical characteristics and objects during their initial identification. When an individual re-enters the monitored area, the system can quickly match them against this pre-stored information using multiple recognition methods, significantly reducing re-identification time while maintaining accuracy.
Solution Approach 2:
The system implements feedback by continuously updating the database with individual information as they move through different areas and by using recognition results from one camera to inform searches in other cameras. This feedback mechanism allows the system to learn from previous identifications and improve the speed and accuracy of subsequent re-identifications.
Data Source
AI summary
Systems and methods for object recognition and association with an identity are disclosed. Systems and methods for object recognition and association with an identity are disclosed. In one embodiment, in an information processing apparatus comprising at least one computer processor, a method for object recognition and association with an identity may include: (1) receiving, from a first image capture device at a facility, a first image or a video; (2) recognizing, in the first image or video, an individual having a physical characteristic and an object in proximity to the individual; (3) associating the physical characteristic and the object with the individual; and (4) storing the association in a database.