Distant Face Recognition via Segmented Camera Prioritization
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Solution Overview
Problem
Conventional surveillance systems using a single video or still camera are limited in monitoring wide areas and capturing high-resolution images of faces with sufficient resolution and contrast for effective face recognition, especially when targets are far away or moving.
Innovation Solution
A system comprising a primary wide-angle camera for detecting people in a wide area, with a prioritizer module to direct secondary high-resolution, pan-tilt-zoom cameras for capturing high-quality facial images, which are then processed by a face recognition module for identification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If a single surveillance camera is used to monitor a wide area, then the coverage area is increased, but the resolution and contrast of captured face images deteriorate
Solution Approach 1:
The system divides the monitoring function into two segments: a wide-angle primary camera for area coverage and multiple high-resolution secondary cameras for detailed face capture. This segmentation allows each camera type to optimize for its specific function, resolving the contradiction between coverage area and image resolution.
Solution Approach 2:
The prioritizer module acts as an intermediary that receives detection data from the primary camera, processes it to identify and prioritize targets, then directs secondary cameras to capture high-resolution images. This intermediary coordination enables the system to maintain both wide coverage and high resolution by intelligently allocating camera resources.
2Measurement precision
If a single surveillance camera focuses on a distant moving target, then the target identification capability is improved, but the system cannot simultaneously monitor wide area for multiple faces
Solution Approach 1:
The system segments the monitoring task between a wide-angle primary camera that continuously scans the entire area and multiple secondary cameras that focus on specific targets. This allows simultaneous wide-area awareness and detailed target identification.
Solution Approach 2:
The prioritizer module performs preliminary processing by detecting all faces in the wide area first, then prioritizing them based on criteria such as proximity to exits or threat level. This preliminary action enables the secondary cameras to focus on the most critical targets while maintaining overall area awareness.
Data Source
AI summary
A method and system for automatic face recognition. A primary and a plurality of secondary video cameras can be provided to monitor a detection area. The primary video camera can detect people present in the detection zone. Data can be then transmitted to a prioritizor module that produces a prioritized list of detected people. The plurality of secondary video cameras then captures a high-resolution image of the faces of the people present in the detection area according to the prioritized list provided by the prioritizor module. The high-resolution images can be then provided to a face recognition module, which is used to identify the people present in the detection area.