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Dynamic and static gesture recognition method and system

A gesture recognition and static recognition technology, applied in the field of image processing, can solve problems such as difficulty in classification

Active Publication Date: 2019-04-12
NANJING FUJITSU NANDA SOFTWARE TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

This method uses electromyographic signals for gesture recognition, which requires wearing a specific acquisition device, and due to individual differences, electrode positions, etc., its classification is very difficult

Method used

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  • Dynamic and static gesture recognition method and system
  • Dynamic and static gesture recognition method and system
  • Dynamic and static gesture recognition method and system

Examples

Experimental program
Comparison scheme
Effect test

specific Embodiment 1

[0148] Step 1: Collect gesture pictures through a common camera.

[0149] Step 2: Perform noise reduction processing on the three channels RGB of the image through the mean filtering method.

[0150] Step 3: Convert the gesture image from RGB color space to YCrCb color space.

[0151] Step 4: Use the ellipse model skin color detection method to make a binary query map according to the formula, such as figure 2 As shown, a pixel value of 255 in the figure represents a skin color pixel point, and a pixel value of 0 represents a non-skin color pixel point. Let the gesture image pixel point P(i,j), C r , C b The values ​​are respectively C rp , C bp , then if in Figure II Midpoint (C rp , C bp ) where the pixel value is 255, then mark point P as a skin-colored area, otherwise mark it as a non-skinned area.

[0152] Step 5: Perform connected domain analysis according to the mark, extract the contour with the largest area as the gesture contour, and calculate its largest ...

specific Embodiment 2

[0191] The present invention conducts recognition experiments on 10 static gestures and 4 dynamic gestures respectively, wherein 200 examples are in each group of static gestures, and 40 examples are in each group of dynamic gestures. See Table 2 and Table 3 for detailed recognition effects.

[0192] Table 2 Statistical Table of Static Gesture Recognition Rate

[0193] gesture

Number of tests

correct number

Recognition rate

0

200

200

100％

1

200

199

99.5％

2

200

198

99％

3

200

198

99％

4

200

197

98.5％

5

200

199

99.5％

6

200

197

98.5％

7

200

199

99.5％

8

200

200

100％

9

200

197

98.5％

[0194] Table 3 Statistical Table of Dynamic Gesture Recognition Rate

[0195] gesture

Number of tests

correct number

Recognition rate

swipe left

50

49

98％

swipe right

50

50

100％...

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Abstract

The invention discloses a dynamic and static gesture recognition method. The method comprises the steps of S1, acquiring gesture images to obtain an image sequence; s2, removing image noise from the acquired gesture image by adopting a mean filtering method; s3, converting the acquired gesture image into a YCrCb space from an RGB color space, establishing an elliptic model, carrying out skin colordetection, segmenting a gesture area, and carrying out binarization processing; s4, constructing a convolutional neural network model and a parameter optimizer thereof, and obtaining a classifier with optimal performance by using the training data; s5, executing gesture static recognition according to the gesture information in the recognition queue; and S6, executing dynamic gesture recognitionaccording to the gesture information in the recognition queue. The gesture data can be collected through a common camera, and the gesture recognition accuracy and stability are improved through gesture segmentation, convolutional neural network classification and motion track constraint.

Description

technical field [0001] The present invention relates to the technical field of image processing, in particular to a dynamic and static gesture recognition method and system. Background technique [0002] Gesture recognition is a natural, convenient and friendly way of human-computer interaction. Capture gesture data through specific sensing devices, use image recognition, machine learning, pattern recognition and other technologies to recognize and understand the types and meanings of gestures, so as to complete the operation and control of the execution device. Gesture recognition technology has broad application prospects in human-computer interaction, mobile terminals, entertainment equipment, smart home, automotive electronics and other fields. [0003] In the existing gesture recognition technology, based on the contact gesture recognition method, it has the advantages of high recognition accuracy and fast speed, but it is not friendly to use; the gesture recognition t...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00
CPCG06V40/28G06V40/113
Inventor 吴凡刘海峰赵阳辛学颖钟静连
Owner NANJING FUJITSU NANDA SOFTWARE TECH
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