Google llc (20240338084). GESTURE DETECTION VIA IMAGE CAPTURE OF SUBDERMAL TISSUE FROM A WRIST-POINTING CAMERA SYSTEM simplified abstract
Contents
GESTURE DETECTION VIA IMAGE CAPTURE OF SUBDERMAL TISSUE FROM A WRIST-POINTING CAMERA SYSTEM
Organization Name
Inventor(s)
Dongeek Shin of San Jose CA (US)
Andrea Colaco of Los Altos CA (US)
Stiven Guillaume Francois Morvan of New York NY (US)
Adam James Banfield of Troy NY (US)
Shahram Izadi of Tiburon CA (US)
GESTURE DETECTION VIA IMAGE CAPTURE OF SUBDERMAL TISSUE FROM A WRIST-POINTING CAMERA SYSTEM - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240338084 titled 'GESTURE DETECTION VIA IMAGE CAPTURE OF SUBDERMAL TISSUE FROM A WRIST-POINTING CAMERA SYSTEM
Simplified Explanation: The patent application describes a system that uses near-infrared imaging to detect hand gestures based on changes in biological flow metrics in the user's wrist.
- An image capture device on a wristband emits infrared radiation into the user's wrist and captures two-dimensional images of the dermal layer.
- Gesture detection circuitry analyzes the sequence of images to determine values of a biological flow metric, such as perfusion index, between frames.
- A trained model generates the metric from the image sequence, mapping these values to specific hand/finger movements that represent different gestures.
Key Features and Innovation:
- Use of near-infrared imaging to detect hand gestures based on biological flow metrics.
- Mapping of biological flow metric values to specific hand/finger movements for gesture recognition.
Potential Applications:
- Human-computer interaction systems.
- Virtual reality and augmented reality applications.
- Healthcare monitoring and rehabilitation devices.
Problems Solved:
- Accurate and non-invasive hand gesture recognition.
- Real-time monitoring of biological flow metrics for various applications.
Benefits:
- Improved user experience in human-computer interaction.
- Enhanced accuracy and efficiency in gesture recognition.
- Non-invasive and continuous monitoring of biological flow metrics.
Commercial Applications: Potential commercial applications include:
- Gesture-controlled devices in gaming and entertainment.
- Healthcare monitoring systems for patient rehabilitation.
- Virtual reality and augmented reality interfaces for immersive experiences.
Questions about Hand Gesture Recognition: 1. How does the use of near-infrared imaging improve hand gesture recognition compared to other methods? 2. What are the potential limitations of using biological flow metrics for gesture detection?
Frequently Updated Research: Ongoing research in this field may focus on improving the accuracy and speed of gesture recognition algorithms, as well as expanding the range of detectable gestures and applications.
Original Abstract Submitted
techniques of operating an ar system include determining hand gestures formed by a user based on a sequence of two-dimensional images through skin of the user's wrist acquired from a near-infrared camera. specifically, an image capture device disposed on a band worn around a user's wrist includes a source of electromagnetic radiation, e.g., light-emitting diodes in the infrared (ir) wavelength band that emit the radiation into the user's wrist and an ir detector which produces the sequence of two-dimensional images of a region within a dermal layer in the user's wrist. from this sequence, gesture detection circuitry determines values of a biological flow metric, e.g., a change in perfusion index (pi) between frames of the sequence, based on a trained model that generates the metric from the sequence. finally, the gesture detection circuitry maps the values of the biological flow metric to specific hand/finger movements that determine a gesture.
