Gesture posture recognition key frame extraction method and device and readable storage medium

An extraction method and key frame technology, applied in the computer field, can solve problems such as inability to extract clear images, achieve the effects of reducing reasoning time, strong anti-interference, and enhancing customer experience
CN112733823AActive Publication Date: 2021-04-30NANCHANG VIRTUAL REALITY RES INST CO LTD
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Patent Information

Authority / Receiving Office
CN Β· China
Current Assignee / Owner
NANCHANG VIRTUAL REALITY RES INST CO LTD
Publication Date
2021-04-30

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Abstract

The invention discloses a gesture recognition key frame extraction method and device and a readable storage medium, and the method comprises the steps: carrying out hand target detection of a target image by a trained hand detection deep learning model, so as to obtain the graphic information of a minimum enclosing rectangle of a hand region; carrying out hand region segmentation to obtain an intermediate image with only hands; calculating the entropy of each frame of intermediate image in the first moment and the entropy of each frame of intermediate image in the second moment; binarizing the intermediate image with the maximum entropy value corresponding to the first moment to obtain a first binarized image, binarizing the intermediate image with the maximum entropy value corresponding to the second moment to obtain a second binarized image, and calculating a hand overlapping rate of the first binarized image and the second binarized image; and determining extraction of the key frame according to the hand overlapping rate. According to the invention, the problem that a clear image cannot be extracted as a predicted key frame in the prior art can be solved.
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Description

technical field

[0001] The present invention relates to the field of computer technology, in particular to a method, device and readable storage medium for extracting key frames for gesture and gesture recognition. Background technique

[0002] Gesture recognition is an important means of human-computer interaction. In VR (Virtual Reality, virtual reality technology) human-computer interaction, users can adjust the volume or control other virtual mobile buttons through virtual gesture recognition.

[0003] Due to hardware processing speed and product experience requirements, gesture estimation needs to meet real-time requirements. Therefore, not all images in the video stream are used for 3D gesture recognition, but some key frames are extracted for recognition. The existing solutions mainly There are fixed time extraction of image frames, random sampling, or frame difference extraction, etc. These methods cannot extract clearer images as key frames for prediction, and blurr...

Claims

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