Image association method and device, storage medium and electronic device

An image correlation and image technology, applied in the computer field, can solve the problems of long target association time, complex and time-consuming algorithms, etc., to achieve the effect of improving efficiency, reducing calculation process, and solving complex algorithms

Pending Publication Date: 2020-04-14
ZHEJIANG DAHUA TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] Embodiments of the present invention provide an image association method and device, a storage medium, and an electronic device to at least solve the problem of object association based on key point detection and aggregation in the related art due to complex algorithms and time-consuming long time problem

Method used

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  • Image association method and device, storage medium and electronic device
  • Image association method and device, storage medium and electronic device
  • Image association method and device, storage medium and electronic device

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Embodiment 1

[0026] In this embodiment, a method for associating images is provided, figure 1 is a flowchart of an image association method according to an embodiment of the present invention, such as figure 1 As shown, the process includes the following steps:

[0027] Step S102, input the image to be processed into the target neural network, and obtain an output result from the output layer of the target neural network, wherein the image to be processed includes a plurality of target images, and each target image includes the first object and The second object, the first object and the second object have an association relationship; the number of channels in the output layer is determined by the following parameters: the number of grids after the image to be processed is divided into multiple grids, the number of frames that form each grid Quantity, position information of the frame in the image to be processed, confidence level, class probability of the first object and the second obje...

Embodiment 2

[0089] In this embodiment, an image association device is also provided, which is used to implement the above embodiments and preferred implementation modes, and what has been described will not be repeated. As used below, the term "module" may be a combination of software and / or hardware that realizes a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, implementations in hardware, or a combination of software and hardware are also possible and contemplated.

[0090] Figure 10 is a schematic structural diagram of an image association device according to an embodiment of the present invention, such as Figure 10 As shown, the device includes: an input module 1002, configured to input the image to be processed into the target neural network, and obtain an output result from the output layer of the target neural network, wherein the image to be processed includes a plurality of target images, Each target...

Embodiment 3

[0100] An embodiment of the present invention also provides a storage medium, in which a computer program is stored, wherein the computer program is set to execute the steps in any one of the above method embodiments when running.

[0101] Optionally, in this embodiment, the above-mentioned storage medium may be configured to store a computer program for performing the following steps:

[0102] S1, input the image to be processed into the target neural network, and obtain an output result from the output layer of the target neural network, wherein, the image to be processed includes a plurality of target images, and each target image includes the first object and the second object Two objects, the first object and the second object have an association relationship; the number of channels in the output layer is determined by the following parameters: the number of grids after the image to be processed is divided into multiple grids, the number of frames forming each grid Quanti...

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Abstract

The invention provides an image association method and device, a storage medium and an electronic device, and the method comprises the steps: inputting a to-be-processed image into a target neural network, and obtaining an output result from the output layer of the target neural network; filtering a plurality of detection frames in the output result according to non-maximum suppression (NMS); anddetermining a detection box with an association relationship from the plurality of filtered detection boxes according to the overlapping degree IoU of each detection box. According to the method and the device, the problem of long time required for target association due to complex algorithm and high time consumption of a target association realization mode based on key point detection and aggregation in the prior art is solved.

Description

technical field [0001] The present invention relates to the field of computers, in particular to an image association method and device, a storage medium and an electronic device. Background technique [0002] In the field of computer vision, target association is to analyze the association of different targets perceived by the visual algorithm. The existing target association methods in the field of computer vision are commonly based on reference human body pose estimation methods, such as Carnegie Mellon’s Open-pose, which first predicts each key point of the human body on the deep network thermal feature map, Then the key points are gathered according to the embedding vector trained by the network, and finally the human body pose is further estimated. Some other methods, such as Google AI, use the frame attention mechanism to link targets, and network input requires continuous feedback from target attention templates. There is also a relationship between targets based o...

Claims

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Application Information

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IPC IPC(8): G06K9/32G06K9/62
CPCG06V10/25G06F18/214
Inventor 于晋川
Owner ZHEJIANG DAHUA TECH
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