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Improved YOLOv4-based shielded pedestrian real-time detection method

A real-time detection and pedestrian technology, applied in the field of computer vision, can solve the problems of insufficient effective feature extraction, loss of important features, missed detection or wrong detection, etc., to prevent the network layer from being too deep, reduce the amount of parameters, and improve detection The effect of precision

Pending Publication Date: 2022-04-12
CHONGQING UNIV OF POSTS & TELECOMM
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  • Abstract
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  • Claims
  • Application Information

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Problems solved by technology

However, this will lead to insufficient effective feature extraction, loss of some important features, resulting in missed or wrong detection

Method used

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  • Improved YOLOv4-based shielded pedestrian real-time detection method
  • Improved YOLOv4-based shielded pedestrian real-time detection method

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Embodiment Construction

[0048] Embodiments of the present invention are described below through specific examples, and those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific implementation modes, and various modifications or changes can be made to the details in this specification based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the diagrams provided in the following embodiments are only schematically illustrating the basic concept of the present invention, and the following embodiments and the features in the embodiments can be combined with each other in the case of no conflict.

[0049] see Figure 1 to Figure 4 , figure 1 Shown is a real-time detection method for occluded pedestrians based on improved YOLOv4, which specifically incl...

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Abstract

The invention relates to an improved YOLOv4-based shielded pedestrian real-time detection method, and belongs to the field of computer vision. The method comprises the following steps: acquiring a data set and processing the data set; clustering is carried out by using a Kmeans + + algorithm, and a final prior frame is generated; feature extraction is carried out by using a trunk feature network fusion channel attention mechanism; utilizing a spatial pyramid SPP module to carry out maximum pooling and merging on feature maps extracted by the backbone feature network; performing feature fusion processing on the last four layers of feature maps obtained by the large residual block in the backbone feature network; performing result prediction on the feature map after feature fusion through a YOLO detection head, predicting the target position and category, and training a model by using a loss function; and applying the optimal weight generated by model training to the model, and putting the test set pictures into the model for testing. The method realizes real-time high-precision detection of sheltered pedestrians, uses few parameters, and is high in detection speed.

Description

technical field [0001] The invention belongs to the technical field of computer vision, and relates to a method for detecting occluded pedestrians in complex scenes. Background technique [0002] With the continuous development of deep learning, it leads the rapid development of the field of target detection. Pedestrian detection is an important direction in the field of target detection. With the development of intelligent monitoring, intelligent transportation and other application fields, pedestrian detection has gradually become a topic with important research value and research significance in the computer field. Due to the requirements of application field scenarios, accurate and real-time pedestrian detection is very necessary. [0003] Traditional pedestrian detection methods are built on hand-crafted features and shallow trainable architectures, combining low-level image features and high-level semantic information from object detectors and scene classifiers to bui...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62G06V40/10G06V10/774G06V10/762G06V10/764
Inventor 梁燕朱清
Owner CHONGQING UNIV OF POSTS & TELECOMM
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