Barrier Access Control Using Face and Body Region Tracking
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Solution Overview
Problem
Existing gate apparatuses struggle to accurately identify and authenticate individuals approaching a barrier, especially when face recognition is obstructed or incomplete, leading to potential errors in determining the authorized person closest to the barrier.
Innovation Solution
The apparatus employs a combination of facial recognition and body region analysis, using a processor to detect and track body regions, determine the closest person based on size and unobstructed boundaries, and control the barrier accordingly, allowing for efficient authentication even when face recognition is incomplete.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If face recognition is used to identify persons approaching the barrier, then authentication capability is improved, but reliability deteriorates when face recognition is obstructed or incomplete
Solution Approach 1:
The patent combines face recognition results with body region analysis results to determine the closest person. When face recognition is obstructed or incomplete, the system merges this with body region size comparison and boundary analysis to maintain authentication reliability, rather than relying on a single identification method.
Solution Approach 2:
The patent introduces body region analysis as an intermediary method between camera imaging and final person identification. The body region analysis (including size measurement and boundary checking) serves as a mediator that can compensate when direct face recognition fails, providing an alternative path to identify the closest person.
2Measurement precision
If only face recognition is used for person identification, then system simplicity is maintained, but measurement precision deteriorates when faces are obstructed
Solution Approach 1:
The patent performs partial face recognition (attempting to recognize faces when visible) but does not rely exclusively on it. Instead, it performs additional body region analysis as a supplementary measure, using only as much complexity as needed when face recognition is insufficient, rather than always applying the full complex system.
Solution Approach 2:
The patent changes the identification parameters dynamically: when face recognition is successful, it uses face features; when faces are obstructed, it switches to using body region size and boundary parameters. This parameter switching allows the system to maintain precision while adapting complexity to actual needs.
3Reliability
If body region analysis is added to improve identification accuracy, then reliability is improved, but device complexity increases
Solution Approach 1:
The patent performs body region analysis preliminarily and in parallel with face recognition, rather than as a sequential backup. The body region extraction, size calculation, and boundary analysis are conducted alongside face recognition processes, so when face recognition fails, the body region data is already available without requiring additional processing steps.
Data Source
AI summary
An apparatus obtains a first image including a plurality of body regions captured at a first time by one or more cameras, each of the plurality of body regions corresponding to a person, among a plurality of persons; detects a first person, among the plurality of persons, by performing facial recognition operation on one of the plurality of body regions in the image obtained from the camera; determines, based on a size of a first body region corresponding to the first person captured in a second image, that the first body region approaching the barrier corresponds to a person closest to the barrier among the plurality of persons; and outputs information to control the barrier to open based on the determination that the first body region corresponds to the person closest to the barrier among the plurality of persons.