Gesture recognition method based on deep learning

A technology of gesture recognition and deep learning, which is applied in the field of gesture recognition based on deep learning, can solve the problems of complex algorithm, expensive and time-consuming calculation of gesture depth information, so as to improve the accuracy of system recognition, solve gesture feature selection, The effect of saving image training time

Active Publication Date: 2014-12-03
DALIAN UNIV OF TECH
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Problems solved by technology

In the usual gesture recognition system, before recognition and classification, gesture feature extraction is required. Since the gesture feature extraction must satisfy the characteristics of rotation, translation and scale invariance, the selected features are very limited, which also limits The recognition accuracy of the gesture recognition system
At the same time, due to the classifiers used in traditional gesture recognition, such as support vector machine (SVM), Boosting, Logistic regression, etc., the structure of these models can basically be regarded as containing only one hidden layer, or there is no hidden layer. These models It belongs to the shallow learning model, which has limited learning ability and cognitive ability to data.
[0003] Dong Lifeng proposed in the document "Static Gesture Recognition and Application Based on Hu Moment and Support Vector Machine" that the Hu moment is selected as the feature of the gesture to be recognized. The Hu moment has the characteristic that it does no

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  • Gesture recognition method based on deep learning
  • Gesture recognition method based on deep learning

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Embodiment Construction

[0022] In order to make the technical solutions and advantages of the present invention more clear, the technical solutions in the embodiments of the present invention are clearly and completely described below in conjunction with the drawings in the embodiments of the present invention:

[0023] Such as figure 1 As shown, a gesture recognition method based on deep learning specifically includes the following steps:

[0024] S1: The median filter method is used to denoise the collected gesture images, and the gray world color balance method is used to eliminate the color shift phenomenon in the gesture images;

[0025] When the median filter method is used to denoise the gesture image, the median filter is used to filter the image, and the red, green and blue components of the pixel at the image midpoint (i, j) are respectively R(i, j) , G(i,j), B(i,j), the window size of the median filter is W 1 ×W 1 , the total number of pixels in this area is W 1 ×W 1 , put this W 1 ×...

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Abstract

The invention discloses a gesture recognition method based on deep learning. The gesture recognition method comprises the following steps: carrying out noise reduction processing to a collected gesture image, and eliminating a color offset phenomenon in the gesture image; locking an area, where a gesture is positioned, in the image by adopting a frame difference method and a color characteristic detection method, and tracking a gesture by adopting a CamShift algorithm to obtain a gesture target; carrying out the deep learning on a gesture target image; and inputting the obtained gesture image to be recognized into a trained deep belief network model to finish the recognition and the classification of the gesture.

Description

technical field [0001] The present invention relates to the technical field of image processing, in particular to a gesture recognition method based on deep learning. Background technique [0002] Gesture is a natural, intuitive and concise way of human-computer interaction. Gesture recognition is based on the video images captured by the computer, using image processing, pattern recognition and other technologies to recognize and understand specific gestures and their meanings in the image, and complete the operation and control of computers and household appliances. Gesture recognition technology has a wide range of applications in human-computer interaction, mobile terminals, information appliances, entertainment games and other fields. In the usual gesture recognition system, before recognition and classification, gesture feature extraction is required. Since the gesture feature extraction must satisfy the characteristics of rotation, translation and scale invariance, t...

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Application Information

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IPC IPC(8): G06K9/66
Inventor 陈喆殷福亮刘奇琴
Owner DALIAN UNIV OF TECH
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