A method of generating object detection model

An object detection and model technology, applied in the field of computer vision, can solve problems such as low accuracy, and achieve the effect of improving accuracy, reducing size, and improving feature receptive field

Inactive Publication Date: 2019-07-30
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

[0040] 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.

[0041] Generally, the SSD object detection model includes a VGG basic network and a pyramid network. Since VGG has a deep network structure with 16 or 19 layers, the model has a large number of parameters and cannot meet the requirements of the mobile terminal. 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 network structure of ...

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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, the object detection model comprising afeature extraction module, a fusion module and a prediction module which are mutually coupled, the feature extraction module being suitable for performing convolution processing on the training imageto generate at least one initial feature map; the fusion module is suitable for performing up-sampling processing on the initial feature map to obtain a feature map after feature fusion; the prediction module is suitable for predicting the category and the position of the target object from the 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 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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IPC IPC(8): G06K9/00G06K9/46G06K9/62
CPCG06V20/00G06V10/454G06F18/214
Inventor 齐子铭李启东陈裕潮张伟李志阳
Owner XIAMEN MEITUZHIJIA TECH
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