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Method for generating object detection model

An object detection and model technology, applied in the field of computer vision, can solve the problem of low accuracy, achieve the effect of improving accuracy and speed, and meeting the requirements of accuracy

Inactive Publication Date: 2019-08-02
XIAMEN MEITUZHIJIA TECH
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Problems solved by technology

This method is fast to detect, but the accuracy is low

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  • Method for generating object detection model
  • Method for generating object detection model
  • Method for generating object detection model

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Embodiment Construction

[0039] Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited by the embodiments set forth herein. Rather, these embodiments are provided for more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.

[0040]Object detection is used to mark the location and category of objects in the image with boxes. Based on the SSD object detection model, it is recognized under different levels of feature maps, which can cover more areas. Generally, the SSD object detection model includes VGG basic network and pyramid network. Because VGG has a deep network structure, there are 16 or more layers. 19 layers, the parameters of the model are too ...

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Abstract

The invention discloses a method for generating an object detection model, and the method comprises the steps: obtaining a training image containing annotation data, and enabling the annotation data to be the position and category of a target object in the training image; inputting the training image into a pre-trained object detection model for processing, with the object detection model comprising a feature extraction module and a prediction module which are coupled to each other, the feature extraction module comprising a deep residual network unit and a convolution processing unit and being suitable for performing convolution processing on the training image to generate at least one feature map; enabling the prediction module to be suitable for predicting the category and the positionof the target object from the at least one feature map; and on the basis of the annotation data and the predicted object category and position, training a pre-trained object detection model to obtaina trained object detection model as a generated object detection model.

Description

technical field [0001] The invention relates to the technical field of computer vision, in particular to a method for generating an object detection model, an object detection method, a computing device and a storage medium. Background technique [0002] Object detection is the basis of many computer vision tasks. It is suitable for locating and identifying one or more known targets in the input image. It is usually applied to scene content understanding, video surveillance, content-based image retrieval, robot navigation and augmented reality, etc. field. [0003] The traditional object detection method is generally divided into three stages: first, extract the candidate frame area, and use the sliding window to traverse the entire image to obtain the possible position of the object; then, extract features from these extracted candidate frame areas. The commonly used method is SIFT (Scale-invariant feature transformation), HOG (Histogram of Oriented Gradients), etc.; final...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62
CPCG06F18/21G06F18/214
Inventor 齐子铭李启东陈裕潮张伟李志阳
Owner XIAMEN MEITUZHIJIA TECH
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