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Model training method and device, gesture recognition method and device, equipment and medium

A gesture recognition and model training technology, applied in the field of deep learning, can solve problems such as large resource consumption and complex algorithm models, and achieve the effect of improving accuracy

Pending Publication Date: 2022-04-12
POWERVISION TECH (SUZHOU) LTD
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Problems solved by technology

In deep learning, generally the deeper and larger the network, the higher the recognition accuracy, but the algorithm model is relatively complex and consumes a lot of resources

Method used

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  • Model training method and device, gesture recognition method and device, equipment and medium
  • Model training method and device, gesture recognition method and device, equipment and medium
  • Model training method and device, gesture recognition method and device, equipment and medium

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Embodiment Construction

[0044] The present invention will be further described in detail with reference to the accompanying drawings. Obviously, the described embodiments are only some of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0045] figure 1 A schematic diagram of the gesture recognition model training process provided by the embodiment of the present invention, the process includes the following steps:

[0046] S101: Acquire gesture sample images in a sample set, and input the gesture sample images into at least two loss networks in a gesture recognition model.

[0047] S102: For the at least two loss networks, determine a training gesture label corresponding to the gesture sample image based on the loss network, and according to the training gesture label and the real...

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Abstract

The invention discloses a model training method and device, a gesture recognition method and device, equipment and a medium. In the embodiment of the invention, when a gesture recognition model is trained, loss function values corresponding to loss networks are determined respectively based on at least two loss networks in the gesture recognition model; and determining a joint loss function value according to the loss function values corresponding to the at least two loss networks, and training the gesture recognition model based on the joint loss function value. On the premise that the number of layers of the network is not increased, at least two loss networks are combined to supervise the training network, the precision of the gesture recognition model can be remarkably improved, and then the precision of gesture recognition is improved under limited computing power.

Description

technical field [0001] The present invention relates to the technical field of deep learning, in particular to a model training and gesture recognition method, device, equipment and medium. Background technique [0002] As the types and quantities of electronic devices increase and their popularity becomes wider and wider, the human-computer interaction method between users and electronic devices has also developed from simple interaction methods using peripherals such as remote controls, mice, and keyboards to using Voice interaction, somatosensory interaction, eye movement interaction and gesture interaction and other diverse interaction methods. Among them, the gesture interaction method has a great demand in many application scenarios because it is more natural and convenient. [0003] Gesture recognition is required in the gesture interaction mode. Under related technologies, gesture recognition is generally performed through deep learning methods. In deep learning, g...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06V40/10G06K9/62G06N3/04G06N3/08G06V10/44G06V10/774G06V10/82
Inventor 毛宁
Owner POWERVISION TECH (SUZHOU) LTD
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