Occupancy Detection Using Color Difference Analysis
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current lighting control systems face challenges in accurately detecting occupancy due to false positives from sources like blinking LEDs, shadows, and reflections, which can lead to inefficient energy usage and inappropriate lighting control.
Innovation Solution
The system employs image sensors and advanced image processing techniques, including color difference analysis, temporal filtering, and centroid tracking, to differentiate between occupancy and non-occupancy events, reducing false positives and improving detection accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If occupancy sensors are used to detect human presence, then lighting control can be automated, but false positives from blinking LEDs, shadows, and reflections reduce detection accuracy
Solution Approach 1:
The patent segments the occupancy detection process into multiple independent analysis stages: color space transformation, component separation, temporal filtering, and centroid tracking. Each stage processes specific features independently before combining results, allowing the system to eliminate false positives from different sources (blinking LEDs, shadows, reflections) through specialized filtering at each stage.
Solution Approach 2:
The patent transforms images from RGB color space to HSV (Hue, Saturation, Value) color space and analyzes specific color components (Hue and Saturation) to detect occupancy. By monitoring color changes over time and comparing them against threshold criteria, the system can distinguish between actual occupancy (which produces consistent color patterns) and false positives (which produce inconsistent or extreme color values).
2Ease of operation
If simple occupancy sensors are used, then the system is easy to operate, but they cannot differentiate between occupancy and environmental changes like shadows and reflections
Solution Approach 1:
The patent introduces an intermediary image processing system between the simple image sensor and the occupancy detection logic. This intermediary performs automated color space transformation, component analysis, and temporal filtering to convert raw image data into reliable occupancy signals, maintaining ease of operation while achieving high detection accuracy through automated differentiation of occupancy from environmental changes.
Solution Approach 2:
The patent replaces traditional mechanical or simple electronic occupancy sensors with an optical-based image sensing system combined with automated image processing. This substitution uses computational analysis of color patterns and temporal changes to detect occupancy, providing both ease of operation (automated detection) and high precision (ability to differentiate occupancy from shadows, reflections, and other environmental changes).
Data Source
AI summary
Occupancy detection for building environmental control is disclosed. One apparatus includes at least one image sensor and a controller, wherein the controller is operative to obtain a plurality of images from the image sensor, determine a color difference image of a color difference between consecutive images, determine areas of the color difference image wherein the color difference is greater than a threshold, calculate a total change area as an aggregate area of the determined areas, create a list of occupancy candidates based on filtering of the determined areas if the total change area is less than a light change threshold, wherein each occupancy candidate is represented by a connected component, track the one or more occupancy candidates over a period of time, and detect occupancy if one or more of the occupancy candidates is detected to have moved more than a movement threshold over the period of time.