Augmented Reality Occupancy Tracking via Virtual Face Objects
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Solution Overview
Problem
Accurately determining occupancy in environments like aircraft cabins, especially under stressful conditions or when manual counting is impractical, is challenging due to the absence of defined seating and the complexity of tracking multiple individuals.
Innovation Solution
The system employs image recognition and augmented reality to detect faces in images from sensors, define facial units based on facial features, associate virtual objects with these units, and calculate occupancy metrics by distinguishing between known and unknown subjects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual counting methods are used to determine occupancy, then simplicity and ease of operation are maintained, but accuracy and efficiency deteriorate under stressful conditions and in crowded environments
Solution Approach 1:
The patent replaces manual mechanical counting methods with an automated image recognition system using cameras and computer vision algorithms. The system captures images, detects faces, and automatically calculates occupancy metrics, eliminating the need for manual intervention while significantly improving accuracy in crowded and stressful conditions.
Solution Approach 2:
The system creates virtual representations (virtual objects) of detected faces to track and count occupants. By generating and managing these digital copies of physical occupants, the system enables automated tracking and prevents double-counting, resolving the contradiction between automation and accuracy.
2Productivity
If automated image recognition is used to track occupancy, then efficiency and accuracy improve, but the complexity of detecting and measuring increases
Solution Approach 1:
The patent segments the complex task of occupancy tracking into distinct modules: image capture, face detection, facial feature analysis, virtual object generation, and occupancy calculation. This segmentation reduces the difficulty of each individual step while maintaining overall system efficiency and productivity.
3Measurement precision
If virtual objects are used as proxies for detected faces, then double counting is prevented and real-time metrics are provided, but device complexity increases
Solution Approach 1:
The system creates virtual objects as digital proxies for each detected face, enabling automated tracking and counting. These virtual objects serve as persistent representations that can be tracked across multiple images and frames, preventing double-counting while providing real-time occupancy metrics. The complexity is managed through automated object management systems.
Data Source
AI summary
Systems, apparatus, and methods for occupancy tracking using augmented reality are disclosed herein. An example apparatus includes memory; instructions; and processor circuitry to execute the instructions to detect a first face in image data, the image data generated by image sensors in an environment and including at least a portion of the environment, the first face corresponding to a subject in the environment; define a first facial unit in the image data based on facial features associated with the first face; associate a first virtual object with the first facial unit in the image data; and determine an occupancy metric for the at least the portion of the environment based on the first virtual object and one or more other virtual objects associated with facial units defined in the image data.