Cooktop Vision Sensing for Accurate Cookware Detection
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Solution Overview
Problem
Existing cookware detection systems lack accuracy and are often costly, leading to false positives and user reluctance to purchase specialized cookware, as they rely on motion sensors, pressure sensors, or expensive cookware with built-in circuitry.
Innovation Solution
A system utilizing a vision sensor and binary classifier to analyze imagery of a cooktop, classifying frames as either depicting cookware or not, and performing responsive operations when cookware is detected, without the need for additional expensive hardware.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If motion sensors are used to detect cookware presence, then detection capability is provided, but false positives occur due to adjacent appliance operation
Solution Approach 1:
The patent replaces motion sensors (mechanical/physical detection) with a vision sensor system that uses image processing and machine learning classifiers to detect cookware. This substitution allows for more accurate identification of cookware by analyzing visual features rather than relying on motion patterns, thereby reducing false positives from adjacent appliance operations.
Solution Approach 2:
The system changes the detection parameters from motion-based metrics to visual feature-based metrics. By using a trained classifier that analyzes multiple image features (shape, texture, position, color), the system achieves more reliable cookware detection that is not triggered by unrelated motion in the environment.
2Reliability
If pressure sensors are used to detect objects on cooktop, then object presence is detected, but accurate cookware identification cannot be achieved
Solution Approach 1:
The patent replaces pressure sensors (mechanical detection) with a vision sensor system that provides both detection and identification capabilities. The vision system captures images and uses classifiers to not only detect that an object is present but also to identify it as cookware based on visual characteristics, eliminating the ambiguity of pressure-based detection.
Solution Approach 2:
The system transitions from one-dimensional pressure sensing to multi-dimensional visual analysis. The vision sensor captures spatial, color, and textural information across multiple dimensions, enabling the classifier to distinguish cookware from non-cookware objects based on comprehensive visual features rather than simple pressure presence.
3Measurement precision
If specialized cookware with built-in circuitry is used, then accurate cookware detection is achieved, but system cost increases significantly
Solution Approach 1:
Instead of requiring specialized cookware with embedded electronics (active components), the patent uses a vision sensor to create optical copies/images of the cookware and analyzes these copies using machine learning classifiers. This passive optical copying approach achieves accurate detection without requiring the cookware itself to be expensive or complex.
Solution Approach 2:
The patent substitutes the need for electronic circuitry in cookware with an optical-mechanical vision sensing system. The detection intelligence is moved from the cookware (requiring built-in electronics) to the sensing system (using cameras and processors), thereby eliminating the need for expensive specialized cookware while maintaining high detection accuracy.
Data Source
AI summary
Systems and methods for cookware detection are provided. One example system includes a vision sensor positioned so as to collect imagery depicting a cooktop. The system includes one or more processors and one or more non-transitory computer-readable media storing instructions that, when executed by the one or more processors, cause the one or more processors to perform operations. The operations include obtaining a frame of imagery depicting the cooktop and using a classifier to classify the frame of imagery as either depicting cookware or not depicting cookware. When the frame is classified as depicting cookware, the operations include performing one or more operations in response to the detected cookware.