Gesture recognition method, an apparatus and a computer program for the same

• US 9,922,241 B2
• Filed: 12/01/2011
• Issued: 03/20/2018
• Est. Priority Date: 12/01/2011
• Status: Active Grant

• Current Assignee: Nokia Technologies Oy (Nokia Corporation)
• Original Assignee: Nokia Technologies Oy (Nokia Corporation)
• Inventors: Li, Jiangwei, Wang, Kongqiao, Xu, Lei
• Primary Examiner(s): Koziol, Stephen R
• Assistant Examiner(s): PATEL, PINALBEN V
• Application Number:
  US14/361,372
• Publication Number:
  US 20140328516A1
• Time in Patent Office: 2,301 Days
• CPC Class Codes: G06V 10/40 Extraction of image or video features
• CPC Class Codes: G06V 10/467 Encoded features or binary features, e.g. local binary patterns [LBP]
• CPC Class Codes: G06V 10/50 by performing operations within image blocks; by using histograms, e.g. histogram of oriented gradients [HoG]; by summing image-intensity values; Projection analysis
• 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

The invention concerns a gesture recognition method for gesture-based interaction at an apparatus. The method comprises receiving one or more images of an object; creating feature images for the received one or more images; determining binary values for pixels in corresponding locations of said feature images and concatenating the binary values to form a binary string for said pixel; repeating the previous step for each corresponding pixel of said feature image to form a feature map and forming a histogram representation of the feature map. The invention also concerns an apparatus and a computer program.

Claims

1. A method comprising:

receiving one or more images of an object,

creating feature images for the received one or more images,

determining binary values for pixels in corresponding locations of said feature images and concatenating the binary values to form a binary string for said pixel,

repeating the previous determination of binary values for each corresponding pixel of said feature image to form a feature map, and

forming a histogram representation of the feature map.

2. The method of claim 1, wherein the received one or more images are captured by an infrared sensor.

3. The method of claim 1, wherein the received one or more images are captured by a camera sensor.

4. The method of claim 1, wherein the received one or more images is an image of a hand.

5. The method of claim 1, further comprising:

using multiple features extractors for determining a shape of the object and for creating the feature images.

6. The method of claim 1, further comprising:

acquiring binary values from at least two feature images to each image location to compose a binary string for the image location in question.

7. The method of claim 1, further comprising one of:

converting the binary string of each corresponding pixel to an integer value and

dividing the feature map into blocks and performing a histogram statistics for each block.

8. The method of claim 7, further comprising:

concatenating histograms of all blocks into a long feature vector to represent an image of the object.

9. The method of claim 1, wherein the received image is a video frame.

20. The method of claim 1, wherein the histogram representation of the feature map reflects reduced noise and reduced frequency relative to the one or more images.

10. An apparatus comprising a processor, and memory including computer program code, the memory and the computer program code configured to, with the processor, cause the apparatus to perform at least the following:

receive one or more images of an object,

create feature images for the received one or more images,

determine binary values for each of a plurality of pixels in corresponding locations of said feature images and concatenating the binary values to form a binary string for each respective pixel,

incorporate each of the binary values for each corresponding pixel of said feature image to form a feature map

form a histogram representation of the feature map representative of spatial distribution features of the one or more images; and

compare each histogram representation to stored histogram representations to determine whether each histogram representation is associated with an object type or a background.

11. The apparatus of claim 10, comprising an infrared sensor configured to capture said one or more images.

12. The apparatus of claim 10, wherein the received one or more images is an image of a hand.

13. The apparatus of claim 10, wherein the computer program code is further configured to, with the processor, cause the apparatus to perform

use multiple features extractors for determining a shape of the object and for creating the feature images.

14. The apparatus of claim 10, wherein the computer program code is further configured to, with the processor, cause the apparatus to perform

acquire binary values from at least two feature images to each image location to compose a binary string for the image location in question.

15. The apparatus of claim 10, wherein the computer program code is further configured to, with the processor, cause the apparatus to perform:

convert the binary string of each corresponding pixel to an integer value.

16. The apparatus of claim 10, wherein the computer program code is further configured to, with the processor, cause the apparatus to perform

divide the feature map into blocks and performing a histogram statistics for each block.

17. The apparatus of claim 16, wherein the computer program code is further configured to, with the processor, cause the apparatus to perform

concatenate histograms of all blocks into a long feature vector to represent an image of the object.

18. The apparatus of claim 10, wherein the received image is a video frame.

19. A computer program product comprising a non-transitory computer readable medium and a computer program embodied thereon, the computer program comprising instructions causing, when executed on at least one processor, at least one apparatus to:

receive one or more images of an object,

create feature images for the received one or more images,

determine binary values for each of a plurality of pixels in corresponding locations of said feature images and concatenating the binary values to form a binary string for each respective pixel,

incorporate each of the binary values for each corresponding pixel of said feature image to form a feature map,

form a histogram representation of the feature map representative of spatial distribution features of the one or more images; and

compare each histogram representation to stored histogram representations to determine whether each histogram representation is associated with an object type or a background.