Image recognition method, device and system

An image recognition and image technology, applied in the field of image recognition, can solve the problems that the accuracy of the model needs to be further improved and the practical application is limited.

Active Publication Date: 2018-11-06
BEIJING KUANGSHI TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] However, the above-mentioned hand gesture recognition method needs to arrange multiple cameras during application, and needs to conduct b

Method used

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  • Image recognition method, device and system
  • Image recognition method, device and system
  • Image recognition method, device and system

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0032] First, refer to figure 1 An example electronic device 100 for implementing the image recognition method, device and system of the embodiments of the present invention will be described.

[0033] Such as figure 1 Shown is a schematic structural diagram of an electronic device. The electronic device 100 includes one or more processors 102, one or more storage devices 104, an input device 106, an output device 108, and an image acquisition device 110. These components pass through a bus system 112 and / or other forms of connection mechanisms (not shown). It should be noted that figure 1 The components and structure of the electronic device 100 shown are only exemplary, not limiting, and the electronic device may also have other components and structures as required.

[0034] The processor 102 can be implemented in at least one hardware form of a digital signal processor (DSP), a field programmable gate array (FPGA), and a programmable logic array (PLA), and the processor...

Embodiment 2

[0041] see figure 2 Shown is a flow chart of an image recognition method, which can be executed by the electronic device provided in the foregoing embodiment, and specifically includes the following steps:

[0042] Step S202, acquiring an image to be recognized.

[0043] In this embodiment of the present invention, the image to be recognized may be an image frame in a video stream collected by a camera, may be an image collected by a camera, or may be a picture in another format, or the like. Wherein, the image to be recognized may be an original image collected by the image acquisition device, an image obtained after target detection based on the original image, or an image modified or generated in other ways. It should be noted here that there may be one camera or multiple cameras with different shooting angles, and the identification may be performed based on image frames acquired by one camera, or based on image frames acquired by multiple cameras.

[0044] Step S204, i...

Embodiment 3

[0075] For the image recognition method provided in Embodiment 2, the embodiment of the present invention provides an image recognition device, see Figure 8 A structural block diagram of an image recognition device shown, including:

[0076] An acquisition module 802, configured to acquire an image to be identified;

[0077] The input module 804 is used to input the image to be recognized into the convolutional neural network model; wherein the convolutional neural network model includes a residual pyramid module, an hourglass module and a cascaded feature pyramid module that are not deformed by translation;

[0078] The recognition module 806 is used to extract the features of the image to be recognized step by step through the residual pyramid module, the hourglass module and the cascaded feature pyramid module in the convolutional neural network model to obtain the recognition result of the image to be recognized; the recognition result includes at least one target point ...

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PUM

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Abstract

The invention provides an image recognition method, device and system, and relates to the technical field of image recognition. The method includes the step of acquiring an image to be recognized; inputting the image to be recognized into a convolution neural network model, wherein the convolution neural network model includes a translation invariance pyramid residual module, a hourglass module and a cascaded pyramid network; extracting the features of the image to be recognized step by step by the translation invariance pyramid residual module, the hourglass module and the cascaded pyramid network of the convolution neural network model to obtain the recognition result of the image to be recognized, wherein the identification result includes a position of at least one target point. The invention can recognize based on the image taken by the monocular camera, and can improve the accuracy of image recognition.

Description

technical field [0001] The present invention relates to the technical field of image recognition, in particular to an image recognition method, device and system. Background technique [0002] Due to the characteristics of high deformation, self-occlusion, mutual occlusion, external occlusion, and background noise of hand gestures, it is very difficult to recognize hand gestures based on ordinary cameras. The prior art usually relies on multiple common cameras to acquire multi-angle images of hand gestures, and then perform hand gesture recognition. [0003] However, the above-mentioned hand gesture recognition method needs to arrange multiple cameras during application, and needs to conduct benchmark tests of the cameras, etc., resulting in very limited practical applications, and the accuracy of the model needs to be further improved. Contents of the invention [0004] In view of this, the purpose of the present invention is to provide an image recognition method, devic...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06K9/46
CPCG06V40/28G06V10/462
Inventor 陈文科姚聪
Owner BEIJING KUANGSHI TECH
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