Depth-Based Privacy Monitoring for Multi-Person Movement Tracking
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Solution Overview
Problem
Current monitoring technologies for an individual's presence and movement in their home are invasive, imprecise, or inconvenient, often requiring visual data that compromises privacy, and struggle to distinguish between individuals or operate in low-light environments.
Innovation Solution
A system that uses depth data, skeleton data, and pixel label data, acquired through a single energy emitter and camera, or two non-overlapping frequency cameras, to monitor presence and movement without revealing visual information, allowing for real-time monitoring without the need for visual light or wearable sensors, and capable of distinguishing between multiple individuals in any lighting conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If visual data (video cameras, facial recognition) is used for monitoring, then monitoring precision and convenience are improved, but privacy is invaded
Solution Approach 1:
The patent extracts only the necessary monitoring information (presence, movement, activity patterns) from the visual data while leaving out identifying features (face, appearance, clothing details). Depth cameras and skeleton tracking extract spatial and motion data without capturing visual identity information, thus achieving precise monitoring while protecting privacy.
Solution Approach 2:
The patent creates abstract representations (depth maps, skeleton models, heat maps) that copy the essential movement and presence information without copying the actual visual appearance. These abstract copies enable monitoring functionality while inherently protecting privacy by design.
2Object-affected harmful factors
If GPS sensors are worn by individuals, then privacy is protected, but monitoring precision and convenience are reduced
Solution Approach 1:
The patent replaces the mechanical/wearable GPS sensor system with an optical sensing system (depth cameras, skeleton tracking) that operates remotely without physical contact. This substitution maintains privacy protection while dramatically improving monitoring precision by capturing detailed movement, posture, and activity information.
3Object-affected harmful factors
If visual images are obfuscated or hidden, then privacy is protected, but the system becomes susceptible to reverse engineering
Solution Approach 1:
The patent inverts the traditional approach by not trying to hide visual images but rather by never capturing them in the first place. The system directly captures depth and spatial information that is inherently non-visual, making reverse engineering to reconstruct images impossible while maintaining strong privacy protection.
4Measurement precision
If multiple persons need to be distinguished, then monitoring precision is improved, but device complexity increases
Solution Approach 1:
The patent applies local quality by assigning unique identification characteristics to different individuals through their distinct movement patterns, posture characteristics, and spatial trajectories. Each person's local movement signature is captured and used for differentiation, enabling precise identification without requiring complex centralized recognition systems.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system provides detailed, high-resolution monitoring of an individual's presence and movement while protecting their privacy, allowing for real-time health status tracking and early warning systems without the need for visual data, reducing hospitalizations and caregiver concerns, and is low-cost, compact, and easy to install.
Implementation Method 1
Depth information may be calculated from a time-of-flight camera
Implementation Method 2
Depth information may be calculated from a laser range finder
Data Source
AI summary
A system for monitoring individuals while protecting their privacy includes at least one energy emitter configured to emit energy onto a field-of-view that may contain an individual, and at least one energy sensor configured to capture reflected energy from within the field-of-view. A spatial measurement module calculates spatial measurements of objects within the field-of-view based on data from the energy sensor. A schematic generation module creates schematic views of objects within the field-of-view, distinguishing human beings from each other and from inanimate objects or animals. Three-dimensional measurements of the individual and environs are transformed into a two-dimensional or other schematic view, allowing ongoing monitoring of the individual while preventing viewing of the individual's face and appearance, and preventing observation of what the individual may be wearing or watching.