Three-dimensional convolutional neural network-based workflow identification method

A technology of three-dimensional convolution and neural network, applied in biological neural network models, neural architecture, data processing applications, etc., can solve problems such as complex recognition process, occlusion, difficult to apply to factory manufacturing environment, etc.

Active Publication Date: 2017-09-22
杭州淘艺数据技术有限公司
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Problems solved by technology

[0003] However, workflow identification technology has its complexity and particularity
First of all, because there are many kinds of machines, transport vehicles, auxiliary equipment and other objects in the production workshop, they are often blocked by each other, and the similarity of different process operations, frequent changes in light intensity in the workshop, all these make video and image analysis and Recognition presents challenges
In addition, the dynamic production workflow process makes the recognition process quite complicated, and it is easy to produce deviations: for example, different tasks in the workflow often have different execution times, and there is no clear definition between the start and end of tasks; these Tasks may even contain both human and mach

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Embodiment Construction

[0049] The present invention will be further described below in conjunction with drawings and embodiments.

[0050] First, define the concept and explain the symbols:

[0051] Frame Difference Threshold t represents the current frame number, l≥1 represents the recursive order, d k is the pixel value of the kth pixel in the inter-frame difference image, max{d k} is the maximum value of the pixel value in the inter-frame difference image, min{d k} is the minimum value of the pixel value in the inter-frame difference map;

[0052] N 1 and N 2 Respectively express satisfaction with the total number of pixels.

[0053] a: Weighted average feature map after weighted average view pooling operation.

[0054] t 1 : The serial number of the pooled feature map after convolution and pooling operations.

[0055] serial number t 1 The weight of the corresponding pooled feature map.

[0056] serial number t 1 The corresponding pooled feature map.

[0057] Secondly, a ...

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Abstract

The invention discloses a three-dimensional convolutional neural network-based workflow identification method. Only different process tasks are divided in advance and different action behaviors are tagged artificially in a video analysis process, so that the automation demand of intelligent manufacturing is not met. An inter-frame difference method with an adaptive threshold is proposed firstly and is mainly used for segmenting out a region of a moving object from a complex background, so that the time complexity of subsequent feature extraction and model training is lowered; secondly, a 3D convolutional neural network is improved to fully adapt to a factory environment with a plurality of monitoring devices, and for different views, a view pooling layer is adopted for fusing views of different angles according to weights; and finally, a new action division method is proposed for performing automatic division on continuous production actions in a video, so that an automated workflow identification process is realized.

Description

technical field [0001] The invention belongs to the technical field of workflow identification and is used for fast and accurate identification and detection of production and manufacturing processes. Through the camera installed in the manufacturing workshop, the entire process of production scheduling on the production line is photographed, and then the video is calculated and processed, so as to protect the personal safety of employees, reduce production costs, ensure product quality, and optimize production scheduling and process specifications. play an important role Background technique [0002] Intelligent manufacturing is the further development direction of manufacturing automation. It widely applies artificial intelligence technology to engineering design, process design, production scheduling, fault diagnosis and other links of industrial manufacturing process, so as to realize intelligent manufacturing process and greatly improve productivity. . As an important...

Claims

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Application Information

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IPC IPC(8): G06Q10/06G06N3/04G06T7/215
CPCG06N3/04G06Q10/0633G06T7/215
Inventor 胡海洋丁佳民陈洁胡华程凯明
Owner 杭州淘艺数据技术有限公司
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