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A method of generating object detection model

An object detection and model technology, applied in the field of computer vision, can solve the problems of low accuracy, achieve the effect of increasing calculation speed, improving flexibility, and improving feature receptive field

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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  • A method of generating object detection model
  • A method of generating object detection model
  • A method of generating object detection model

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Embodiment Construction

[0041] Hereinafter, exemplary embodiments of the present disclosure will be described in more detail 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 can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.

[0042] Generally, SSD object detection models include VGG basic network and pyramid network. Because VGG has a deep network structure with 16 or 19 layers, the model has a large amount of parameters and cannot meet the requirements of mobile terminals. In order to achieve real-time object detection and make the model meet the requirements of mobile memory and computing speed, this solution improves the networ...

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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 being suitable for performing convolution processing on the training image to generate at least one initial feature map; enabling the prediction module to be suitable for predicting the category and the position of 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 obtain a trained object detection model as a generated object detection model.

Description

Technical field [0001] The present invention relates to the field of computer vision technology, 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 targets in the input image. It is usually used in scene content understanding, video surveillance, content-based image retrieval, robot navigation and augmented reality, etc. field. [0003] Traditional object detection methods are generally divided into three stages: First, extract the candidate frame area, and use a sliding window to traverse the entire image to obtain the possible position of the object; then, extract features from these extracted candidate frame areas. Commonly used methods are SIFT (Scale Invariant Feature Transformation), HOG (Histogram of Oriented Gradients), etc.; Finally, input the...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/46G06K9/62
CPCG06V10/443G06F18/2451G06F18/214
Inventor 齐子铭李启东陈裕潮张伟李志阳
Owner XIAMEN MEITUZHIJIA TECH
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