Depth Image Interfacing Region Detection via Local Depth Comparison
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Solution Overview
Problem
Current natural user interface technologies face challenges in accurately detecting user inputs from depth images, particularly in distinguishing hand regions from other body parts based on depth differences, leading to inefficiencies in motion recognition.
Innovation Solution
A method and apparatus that compare the depth of a first region to a second external region in a depth image, classify points within the first region as interfacing regions based on depth differences, and select appropriate regions to detect user inputs by calculating distance information and identifying end-points, thereby enhancing user input detection accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If depth-based region comparison is used to detect user inputs, then user input detection accuracy is improved, but computational complexity increases
Solution Approach 1:
The detection process is segmented into distinct stages: selecting candidate points in the depth image, defining first and second regions around each candidate point, comparing depth values between these regions, and classifying interfacing regions based on depth differences. This segmentation allows the complex detection task to be broken down into manageable steps, improving accuracy while controlling computational complexity through systematic processing.
Solution Approach 2:
The patent applies local quality analysis by examining depth characteristics in specific local regions (first and second regions) around candidate points rather than analyzing the entire depth image globally. By focusing computational resources on localized depth comparisons around potential interfacing points, the system achieves high detection accuracy while minimizing overall computational complexity.
2Measurement precision
If multiple points are analyzed in depth image to detect interfacing region, then detection accuracy is improved, but processing time increases
Solution Approach 1:
The patent implements preliminary action by first selecting candidate points and defining regions before performing depth comparisons. By pre-establishing the first and second regions around candidate points and preparing depth comparison criteria in advance, the system reduces processing time during the actual detection phase while maintaining high accuracy through thorough multi-point analysis.
3Measurement precision
If depth difference threshold is applied to classify interfacing region, then classification accuracy is improved, but false detection rate increases
Solution Approach 1:
The patent employs parameter changes by dynamically adjusting the depth difference threshold based on the specific characteristics of the depth image and candidate points. Rather than using a fixed threshold, the system adapts the threshold parameter to local depth variations, improving classification accuracy while reducing false detections by accounting for different depth ranges and scene conditions.
Data Source
AI summary
An apparatus for detecting an interfacing region in a depth image detects the interfacing region based on a depth of a first region and a depth of a second region which is an external region of the first region in a depth image.