Gesture recognition method

A gesture recognition and gesture technology, applied in the field of gesture recognition, can solve problems such as failure to meet real-time requirements, complex recognition algorithms, and reduced recognition efficiency, and achieve the effects of easy implementation, high recognition efficiency, and improved efficiency and accuracy

Active Publication Date: 2017-08-11
HUAZHONG NORMAL UNIV
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Problems solved by technology

[0004] (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

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Embodiment Construction

[0052]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. In this example, Kinect is used to obtain the depth image sequence and the position of some joints of the human body (palm and elbow) in real time, and image processing technology is used 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.

[0053] The technical solutions of the present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0054] Such as figure 1 As shown, the specific implementation of this embodiment includes the following steps:

[0055] Step 1, obtain the depth image sequence in real time through Kinect;

[0056] According to the reflection time of the light from the camera to the object, the ...

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Abstract

The invention belongs to the technical field of gesture recognition, and relates to a gesture recognition method. The method comprises the following steps: acquiring a depth image sequence in real time via Kinect; acquiring the positions of a palm center and an elbow center in real time via the Kinect, and extracting a hand contour according to the depth information of each frame of image; calculating a fingertip position and a finger root position according to the palm center position, the elbow center position and the hand contour, and extracting features; matching the features extracted in step 3 with gesture features in a template library, entering a classifier, selecting the most proximate gestures as recognized gestures according to the classification standard of the classifier, and saving the gesture recognized in each frame into a queue Q; analyzing the recognition results of the frame and the front four frames in the queue Q, and selecting the gestures of a largest quantity as the final recognition result. The method can quickly and accurately recognize the gestures of an operator by acquiring depth information using Kinect and in combination with a digital image analysis technology.

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 technology is 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 amb...

Claims

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Application Information

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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
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