Hand gesture recognition method based on switching Kalman filtering model

A Kalman filter and gesture recognition technology, applied in the field of human-computer interaction, can solve problems such as high computational complexity, narrow application range, and poor real-time performance

Inactive Publication Date: 2014-09-17
XIAN TECHNOLOGICAL UNIV
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Problems solved by technology

[0007] The purpose of the present invention is to provide a hand gesture recognition method based on a switched Kalman filter model, whi

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  • Hand gesture recognition method based on switching Kalman filtering model
  • Hand gesture recognition method based on switching Kalman filtering model
  • Hand gesture recognition method based on switching Kalman filtering model

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Embodiment Construction

[0044] The present invention will be described in detail below with reference to the accompanying drawings and specific embodiments.

[0045] The related technology in the present invention is introduced as follows:

[0046] (1) Gesture segmentation technology based on skin color model: skin color is the most obvious and simple feature that distinguishes the face and hands from the surrounding environment, so by determining the accurate skin color area threshold conditions, the face and hands area can be located. The image color space of the video is RGB color space, but the skin color of the human body is greatly affected by the brightness in the RGB space, which makes it difficult to separate the skin color points from the non-skin color points. Skin tones are very different, mainly due to differences in saturation and brightness, while skin tones are not very different in hue. In the chromaticity space, the HSV color space uses three dimensions of hue H, saturation S and b...

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Abstract

The invention discloses a hand gesture recognition method based on a switching Kalman filtering model. The hand gesture recognition method based on a switching Kalman filtering model comprises the steps that a hand gesture video database is established, and the hand gesture video database is pre-processed; image backgrounds of video frames are removed, and two hand regions and a face region are separated out based on a skin color model; morphological operation is conducted on the three areas, mass centers are calculated respectively, and the position vectors of the face and the two hands and the position vector between the two hands are obtained; an optical flow field is calculated, and the optical flow vectors of the mass centers of the two hands are obtained; a coding rule is defined, the two optical flow vectors and the three position vectors of each frame of image are coded, so that a hand gesture characteristic chain code library is obtained; an S-KFM graph model is established, wherein a characteristic chain code sequence serves as an observation signal of the S-KFM graph model, and a hand gesture posture meaning sequence serves as an output signal of the S-KFM graph model; optimal parameters are obtained by conducting learning with the characteristic chain code library as a training sample of the S-KFM; relevant steps are executed again for a hand gesture video to be recognized, so that a corresponding characteristic chain code is obtained, reasoning is conducted with the corresponding characteristic chain code serving as input of the S-KFM, and finally a hand gesture recognition result is obtained.

Description

technical field [0001] The invention belongs to the technical field of human-computer interaction, and in particular relates to a gesture recognition method based on a switched Kalman filter model. Background technique [0002] Human-computer interaction technology is a general term for the technology that realizes the communication between humans and computers. With the rapid development of computers, this field has profound research significance and broad application prospects, and has become a research hotspot at home and abroad. At present, human-computer interaction is mainly realized through voice input and action instructions. Because speech is easily affected by the external environment and the inconsistency of language types, this increases the complexity of human-computer interaction and reduces the accuracy of interaction. 70% of the communication between people is achieved through body language. As one of the simplest and most direct body language, gestures conv...

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Application Information

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IPC IPC(8): G06K9/66G06K9/00G06T5/00
Inventor 肖秦琨侯亭亭高嵩
Owner XIAN TECHNOLOGICAL UNIV
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