Robot Cleaner Gesture Recognition Using Arm Angle Histograms
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Solution Overview
Problem
Current gesture recognition technologies for robot cleaners face limitations due to the use of low-quality single black and white images, requiring additional sensors and struggling with real-time processing, especially when the user's size is small or the image quality is poor.
Innovation Solution
A method and apparatus that utilize a camera to extract an arm image from the robot cleaner's image, divide it into cell images, calculate histograms, determine primary angles, and score each cell image to accurately calculate the arm's angle, allowing the robot cleaner to execute functions based on the arm's position.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a single black and white image is used for gesture recognition, then the device complexity is reduced, but the measurement precision deteriorates
Solution Approach 1:
The image is divided into multiple cell images (e.g., 3x3 grid), and histograms are calculated for each cell to extract local features. This segmentation allows the system to process low-quality images by breaking them into manageable parts and combining their information
Solution Approach 2:
The patent transitions from spatial image data to histogram data, adding a dimensional transformation. By converting pixel information into histogram distributions across multiple cells, the system extracts meaningful gesture features even from low-resolution black and white images
2Productivity
If real-time gesture recognition is implemented, then the productivity is improved, but the calculation complexity increases
Solution Approach 1:
Dividing the image into cells and calculating histograms for each cell enables parallel processing of different regions, reducing overall calculation time and enabling real-time gesture recognition
Solution Approach 2:
The patent extracts only the essential histogram features from each cell image rather than processing all pixel data. This extraction of key characteristics significantly reduces calculation complexity while maintaining recognition accuracy
3Adaptability or versatility
If the user size is small in the image, then the adaptability is improved, but the measurement precision deteriorates
Solution Approach 1:
By dividing the image into multiple cells, the system can detect arm gestures even when the user occupies a small portion of the image. The histogram analysis in each cell can identify arm-related patterns regardless of the user's overall size in the frame
Solution Approach 2:
The patent applies different analysis methods to different regions (cells) of the image. By focusing on local histogram characteristics in each cell rather than requiring global image quality, the system can detect gestures even when the user is small in the overall image
Data Source
AI summary
A robot cleaner is provided. The robot cleaner includes a camera obtaining an image including a user; and a control unit extracting, an arm image including an arm, from the image obtained by the camera, calculating an angle of an arm of an user from the arm image, and determining a function intended by the angle of the arm calculated to control execution of the function.