3D FINGER POSTURE DETECTION AND GESTURE RECOGNITION ON TOUCH SURFACES

• US 20130009896A1
• Filed: 07/09/2012
• Published: 01/10/2013
• Est. Priority Date: 07/09/2011
• Status: Abandoned Application

• Current Assignee: NRI R&D Patent Licensing, LLC (Advanced Touchscreen and Gesture Technologies, LLC)
• Original Assignee: Lester F. Ludwig
• Inventors: ZALIVA, Vadim
• Application Number:
  US13/544,960
• Publication Number:
  US 20130009896A1
• Time in Patent Office: Days
• US Class Current: 345/173
• CPC Class Codes: G06F 3/0416 Control or interface arrangements specially adapted for digitisers
• CPC Class Codes: G06F 3/044 by capacitive means
• CPC Class Codes: G06F 3/04883 for inputting data by handwriting, e.g. gesture or text

Abstract

The invention provides 3D touch gesture recognition on touch surfaces incorporating finger posture detection and includes a touch user interface device in communication with a processing device. The interface device includes a sensor array for sensing spatial information of one or more regions of contact and provides finger contact information in the form of a stream of frame data. A frame is read from the sensor array, subjected to thresholding, normalization, and feature extraction operations to produce a features vector. A multi-dimensional gesture space is constructed having desired set of features, each represented by a space dimension. A gesture trajectory is a sequence of transitions between pre-calculated clusters, and when a specific gesture trajectory is detected, a control signal is generated.

Claims

1. A system for 3D gesture recognition on touch surfaces, the system comprising:

a touch user interface device including a sensor array configured to sense finger contact information associated with one or more regions of contact providing the finger contact information in the form of a stream of frame data; and

a processing device in communication with the touch user interface device configured to;

read frame data from the sensor array;

produce modified frame data by performing thresholding and normalization operations on the frame data,

produce a features vector by extracting at least one feature from the modified frame data;

create a gesture trajectory in a multi-dimensional gesture space wherein the multi-dimensional gesture space comprises a plurality of feature vectors, and wherein the gesture trajectory is a sequence of transitions between regions of the multi-dimensional gesture space;

detect a specific gesture; and

generate a control signal in response to the specific gesture.

2. The system of claim 1, wherein the processing device is further configured to implement a principle component analysis operation.

3. The system of claim 1, wherein the processing device is further configured to implement a Kalman filter operation.

4. The system of claim 1, wherein the multi-dimensional gesture space comprises a desired set of features, each feature represented by an associated dimension in the gesture space.

5. The system of claim 1, wherein the extraction of at least one feature further comprises high performance segmentation using Connected Component Labeling with subsequent label merging employing a Hausdorff metric is used to implement multi-touch capabilities.

6. The system of claim 1, wherein the extraction of at least one feature further comprises high performance segmentation with subsequent label merging employing a metric similar to but differing from a Hausdorff metric is used to implement multi-touch capabilities.