A gesture recognition method
A gesture recognition and gesture technology, applied in the field of gesture recognition, can solve the problems of inability to meet real-time requirements, complex recognition algorithms, and low recognition efficiency, and achieve the effects of easy implementation, low algorithm complexity, and improved efficiency and accuracy.
Active Publication Date: 2019-12-24
HUAZHONG NORMAL UNIV
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[0003] (1) Algorithms based on color images and skin color segmentation are susceptible to factors such as lighting conditions, complex backgrounds, and skin color changes. In an environment with insufficient lighting or hand color differences (such as doctors wearing gloves during surgery) Under this condition, the recognition efficiency will be greatly reduced, which will affect the practicability
[0004] (2) The recognition algorithm is complex and the amount of calculation is large, which cannot meet the real-time requirements
[0005] (3) In the case of gesture rotation, translation and scaling, the recognition rate is not high
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[0064] Based on the research on gesture recognition, the present invention takes the relative positions of fingertips, palm centers and elbow centers as a breakthrough to recognize gestures. This example uses Kinect to obtain the depth image sequence and the position of some joints (palm and elbow) of the human body in real time, and uses image processing technology to analyze the obtained data, so that the preset gestures can be recognized more accurately. The gestures in this example are traditional Chinese counting gestures one to ten.
[0065] The technical solutions of the present invention will be further described below in conjunction with the accompanying drawings and embodiments.
[0066] Such as figure 1 As shown, the specific implementation of this embodiment includes the following steps:
[0067] Step 1, obtain the depth image sequence in real time through Kinect;
[0068] According to the reflection time of the light from the camera to the object, the distance ...
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The invention belongs to the technical field of gesture recognition, and relates to a gesture recognition method, comprising the following steps: obtaining a sequence of depth images in real time through Kinect; Body contour; according to the palm center position, elbow center position and hand contour, calculate the fingertip position and finger root position, extract features; match the features extracted in step 3 with the gesture features in the template library, enter the classifier, According to the classification standard of the classifier, select the closest gesture as the recognized gesture, and save the recognized gesture of each frame in the queue Q; analyze the recognition results of this frame and the previous four frames in the queue Q, and select the number of occurrences The most gestures are used as the final recognition result. The present invention uses Kinect to obtain depth information and combines digital image analysis technology to quickly and accurately identify the operator's gestures.
Description
technical field [0001] The invention belongs to the technical field of gesture recognition, and relates to a gesture recognition method. Background technique [0002] Gestures are currently one of the most natural and intuitive ways of human-computer interaction. The existing gesture recognition technologies are mainly divided into two types. One is gesture recognition based on data gloves, which require users to wear special data gloves to track and mark the movement trajectory and timing information of human hands in spatial coordinates, and then pass signal Processing to achieve the purpose of gesture recognition, this method requires the purchase of expensive equipment and has low practicability. The other is gesture recognition based on computer vision, which mainly uses ordinary cameras to obtain image data including hands, and recognizes gestures through data processing and analysis. This method has poor real-time performance, and the detection effect depends on the ...
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IPC IPC(8): G06K9/00G06K9/62
CPCG06V40/28G06F18/24
Inventor 田元王学璠陈加姚璜王志峰
Owner HUAZHONG NORMAL UNIV