Depth Camera Hand Tracking at Close Range
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current 3D imaging devices are unable to reliably detect and track hands and fingers at close distances, limiting their capability for accurate hand and finger gesture recognition in interactive systems, especially in environments where users are closer than 1 meter from the camera.
Innovation Solution
A method for detecting, localizing, and segmenting hands and fingers using depth images from a time-of-flight camera without relying on color information or hand models, employing morphological image processing and tracking techniques to isolate and model hand extremities and fingers within a 3D scene.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If 3D imaging devices are used to detect hands and fingers at distances greater than 1 meter, then the device can operate in a standard range, but the detection accuracy and ability to detect small objects like fingers deteriorates
Solution Approach 1:
The patent changes the operational parameter of detection distance to be less than 1 meter (close interaction range), which fundamentally alters the performance characteristics of the 3D imaging device. This parameter change enables the device to achieve sufficient measurement precision for hand and finger detection while maintaining reliable operation, resolving the contradiction between standard operating range and detection accuracy
2Measurement precision
If 3D imaging devices operate in close interaction mode (less than 1 meter), then the detection accuracy for hands and fingers improves, but the device complexity and processing requirements increase
Solution Approach 1:
The patent segments the detection process into distinct stages: initial hand detection using skin color probability, followed by separate finger detection and tracking processes. This segmentation allows each sub-process to be optimized independently, managing the overall processing complexity while maintaining high detection accuracy for hands and fingers in close interaction mode
3Adaptability or versatility
If skin color detection is used to detect hands and face, then the detection capability in close interaction environment is enabled, but the reliability deteriorates under varying illumination conditions
Solution Approach 1:
The patent implements a Bayesian classifier that uses feedback from multiple features (skin color probability, depth information, spatial relationships) to continuously refine detection reliability. The system adjusts its detection criteria based on the accumulated evidence from different sensor modalities, maintaining reliable hand and face detection across varying illumination conditions in close interaction environments
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
Enables accurate detection and tracking of hands and fingers at close distances, allowing for effective hand and finger gesture recognition and control of computerized systems in close interaction contexts, improving the resolution and accuracy of human-to-machine interfaces.
Implementation Method 1
3D time-of-flight (ToF) cameras, it becomes possible to detect and to track features at different distances from the camera sensor
Data Source
AI summary
Described herein is a method for detecting, identifying and tracking hand, hand parts, and fingers on the hand (500) of a user within depth images of a three-dimensional scene. Arms of a user are detected, identified, segmented from the background of the depth images, and tracked with respect to time. Hands of the user are identified and tracked and the location and orientation of its parts, including the palm and the fingers (510, 520, 530, 540, 550) are determined and tracked in order to produce output information enabling gesture interactions.