Surveillance System Integrating Mobile Location Data for Identity Resolution
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Solution Overview
Problem
Surveillance systems often fail to identify individuals in video feeds due to unclear facial images, poor lighting, or the use of disposable phones and aliases, limiting the availability of identity and mobile phone number information.
Innovation Solution
Integrating a mobile phone location system with surveillance systems to associate individuals in video feeds with their mobile phone information, using facial recognition and projective geometry to enhance identification and overlay relevant data onto the video stream, including communication and financial transactions, social connections, and personal information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If facial recognition is used to identify persons in video feeds, then person identity information can be obtained, but clear facial pictures are required which may not be available due to poor lighting or intentional hiding
Solution Approach 1:
The patent introduces mobile phone location data as an intermediary to bridge the gap between video surveillance and person identification. When facial recognition fails due to poor image quality, the system uses mobile phone location information (obtained through triangulation or GPS) as an alternative key to identify the person by matching the phone's location with the video feed location, thereby compensating for the lack of clear facial pictures
Solution Approach 2:
The system implements multiple identification methods that can serve different functions depending on conditions: facial recognition is used when clear images are available, while mobile phone location matching serves as a universal alternative when facial recognition fails. This multi-functional approach ensures person identification can be achieved regardless of lighting conditions or whether the person is hiding their face
2Loss of information
If mobile phone location system is integrated with surveillance system, then person identity and phone number information can be associated, but system complexity increases
Solution Approach 1:
The patent merges the mobile phone location system with the surveillance system by integrating their data processing functions. The mobile phone's location information (obtained through triangulation using base station signals) is combined with video feed location data in a unified processing framework, allowing the system to correlate phone numbers with video images through their shared location parameter without requiring separate independent systems
Solution Approach 2:
The system uses the mobile phone's own location capabilities (GPS or triangulation) to provide the identification key. The phone essentially serves itself by providing its location data, which the surveillance system then uses to identify the person. This self-service approach reduces the need for additional external identification infrastructure
3Loss of information
If multiple data sources are integrated to provide comprehensive person information, then information completeness improves, but data processing time and system complexity increase
Solution Approach 1:
The system performs preliminary actions by continuously tracking and storing mobile phone location information before it is needed for identification. Mobile phone locations are monitored in advance and correlated with surveillance zones, so when a person of interest appears in video feeds, the identification can be quickly made by matching the pre-collocated phone data with the current video location, rather than processing everything in real-time
Data Source
AI summary
Data from a wireless network location system is used in conjunction with the known geographic location of a video surveillance area such that the system according to the present invention infers that a person who appears in an image in the video is the user of a mobile phone estimated to be at the person's location. When facial recognition is applied and the person's identity is thus recognized, an association is generated as between the identity according to the facial recognition and the identity of the co-located mobile phone. This association can be critical when there is no personal identification available for a mobile phone such as a pre-paid mobile.