GESTURE IDENTIFICATION WITH NATURAL IMAGES

• US 20180129875A1
• Filed: 12/21/2017
• Published: 05/10/2018
• Est. Priority Date: 10/08/2012
• Status: Active Grant

• Current Assignee: PixArt Imaging Incorporated
• Original Assignee: PixArt Imaging Incorporated
• Inventors: YANG, SHU-SIAN
• Granted Patent: US 10,198,627 B2
• Time in Patent Office: Days
• CPC Class Codes: G06V 40/28 Recognition of hand or arm movements, e.g. recognition of deaf sign language static hand signs G06V40/113

Abstract

A method for gesture identification with natural images includes generating a series of variant images by using each two or more successive ones of the natural images, extracting an image feature from each of the variant images, and comparing the varying pattern of the image feature with a gesture definition to identify a gesture. The method is inherently insensitive to indistinctness of images, and supports the motion estimation in axes X, Y, and Z without requiring the detected object to maintain a fixed gesture.

Claims

1. A method for gesture identification independent of color temperature with natural images for adapting to indistinct images and gestures as fast swipes, comprising the steps of:

A.) generating a time-based series of images;

B.) selecting successive images from the series of the images, and using the entire frames of the selected images to generate a plurality of variant images;

C.) extracting a plurality of image features from the variant images; and

D.) comparing a varying pattern of the image features with a gesture definition to identify a gesture;

wherein the method does not comprise the steps of;

detecting a profile of the selected images,

recognizing the shape of a gesture in each selected image, and

finding out a position of the gesture in each selected image.

2. The method of claim 1, wherein the step B comprises the step of subtracting between the images being successive in terms of time.

3. The method of claim 1, wherein the step C comprises the step of screening pixels of the variant images by a threshold for calculating the image features.

4. The method of claim 1, wherein the step C comprises the step of calculating a barycenter, a standard deviation or a variance of the variant images as the image features.

5. The method of claim 1, wherein the step D comprises the step of processing the image features by a frequency analysis to determine the varying pattern.

6. A method for gesture identification independent of the color temperature with natural images for adapting to indistinct images and gestures as fast swipes, comprising the steps of:

A.) generating a time-based series of images;

B.) comparing the entire frames of successive images to generate a plurality of differential images from the series of the images; and

C.) comparing the differential image with a gesture definition to identify a gesture;

wherein the method does not comprise the steps of;

detecting a profile of the selected images,

recognizing the shape of a gesture in each selected image, and

finding out a position of the gesture in each selected image.

7. The method of claim 6, wherein the step B comprises the step of subtracting between the images being successive in terms of time.

8. The method of claim 6, wherein the step C comprises the step of screening pixels of the differential images by a threshold for calculating image features.

9. The method of claim 6, wherein the gesture includes a hand left motion, a hand right motion or a hand rotation motion.

10. The method of claim 6, wherein the step C comprises the step of processing the differential images by a frequency analysis to determine a varying pattern.

11. The method of claim 10, wherein the step C comprises the step of comparing the varying pattern of the differential images with the gesture definition to identify the gesture.