System and method of dynamically generating a frequency pattern to realize the sense of touch in a computing device

• US 9,046,926 B2
• Filed: 04/01/2013
• Issued: 06/02/2015
• Est. Priority Date: 12/17/2012
• Status: Expired due to Fees

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Mohammed, Siddique, Shanmugam, Dhandapani
• Primary Examiner(s): Sasinowski, Andrew
• Application Number:
  US13/854,220
• Publication Number:
  US 20140168111A1
• Time in Patent Office: 792 Days
• Field of Search: 345173-178
• US Class Current: 1/1
• CPC Class Codes: G06F 3/016 Input arrangements with force or tactile feedback as computer generated output to the user

Abstract

Systems and methods for providing tactile feedback. A method for providing tactile feedback, comprises extracting a plurality of features from a visual representation of a physical object, wherein the extracting is performed using at least one image processing technique, generating a variable frequency pattern corresponding to the extracted features, sending the variable frequency pattern to a computing device, and generating the tactile feedback via the computing device in response to a stimulation applied by a user, wherein the tactile feedback is based on the variable frequency pattern.

Claims

1. A method for providing tactile feedback, comprising:

extracting a plurality of features from a visual representation of a physical object, wherein the extracting is performed using at least one image processing technique;

generating a variable frequency pattern corresponding to the extracted features;

sending the variable frequency pattern to a computing device;

assigning values within a range for each of the plurality of features, wherein the values correspond to actual characteristics of the physical object, wherein an actual characteristic includes at least texture of the physical object, and a value within the range corresponding to the texture is based on a degree of the texture;

weighting the values, wherein weights applied to the values are based on an importance of each value in connection with accurate identification of the extracted features of the physical object via the tactile feedback; and

generating the tactile feedback via the computing device in response to a stimulation applied by a user, wherein the tactile feedback is based on the variable frequency pattern.

2. The method of claim 1, further comprising:

segmenting the visual representation into a plurality of portions; and

calculating a frequency value for each of the plurality of portions based on the weighted values, wherein a weighted value for an actual characteristic of the physical object in a first portion of the plurality of portions differs from a weighted value for the actual characteristic in a second portion of the plurality of portions.

3. The method of claim 2, further comprising:

mapping the variable frequency pattern for each frequency value of the plurality of portions.

4. The method of claim 1, wherein the variable frequency pattern is sent to the computing device as meta data.

5. The method of claim 1, wherein the tactile feedback comprises a vibration corresponding to the variable frequency pattern.

6. The method of claim 1, wherein the extracted features comprise the texture and at least one of temperature, softness/hardness, moisture content, color and size.

7. The method of claim 1, wherein the computing device is a mobile device.

8. The method of claim 1, wherein the tactile feedback includes a multi-dimensional time-varying pattern of vibration.

9. The method of claim 1, further comprising:

segmenting the visual representation into a plurality of portions;

calculating a frequency value for each of the plurality of portions corresponding to the extracted features; and

mapping the variable frequency pattern for each frequency value of the plurality of portions.

10. The method of claim 1, further comprising:

segmenting the visual representation into a plurality of portions;

wherein a weighted value for an actual characteristic of the physical object in a first portion of the plurality of portions differs from a weighted value for the actual characteristic in a second portion of the plurality of portions.

11. The method of claim 1, wherein another actual characteristic includes at least softness/hardness of the physical object, and a value within the range corresponding to the softness/hardness is based on a degree of the softness/hardness.

12. The method of claim 1, further comprising:

segmenting the visual representation into a plurality of portions;

wherein the degree of the texture in a first portion of the plurality of portions and a corresponding range value based on the degree of the texture in the first portion differ from the degree of the texture in a second portion of the plurality of portions and a corresponding range value based on the degree of the texture in the second portion.

13. The method of claim 1, wherein the weights are dynamically learned.

14. A method for providing tactile feedback, comprising:

extracting a plurality of features from a visual representation of a physical object, wherein the extracting is performed using at least one image processing technique;

generating a variable frequency pattern corresponding to the extracted features;

sending the variable frequency pattern to a computing device;

assigning values within a range for each of the plurality of features, wherein the values correspond to actual characteristics of the physical object, wherein a value within the range corresponding to an actual characteristic is based on a degree of the actual characteristic;

weighting the values, wherein weights applied to the values are based on an importance of each value in connection with accurate identification of the extracted features of the physical object via the tactile feedback; and

generating the tactile feedback via the computing device in response to a stimulation applied by a user, wherein the tactile feedback is based on the variable frequency pattern.

15. The method of claim 14, wherein the weights are dynamically learned.