Pedestrian detection method based on deep learning

A pedestrian detection and deep learning technology, applied in the field of pedestrian detection based on deep learning, can solve the problems of missed detection, false detection and long time consumption, and achieve the effect of reducing the number of network structure layers, reducing missed detection, and fast speed

Pending Publication Date: 2021-06-25
QUFU NORMAL UNIV +1
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Problems solved by technology

[0006] In view of this, the present invention provides a pedestrian detection method based on deep learning. The purpose of the present invention is to solve the problems of missed detection, false detection and long time consumption caused by dense pedestrians or occlusions and pedestrian postures in the SSD algorithm. , optimize the SSD algorithm, and provide a pedestrian detection method based on deep learning to improve the accuracy, speed and small target pedestrian detection performance of pedestrian detection

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  • Pedestrian detection method based on deep learning
  • Pedestrian detection method based on deep learning
  • Pedestrian detection method based on deep learning

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Embodiment Construction

[0049] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0050] The embodiment of the present invention discloses a pedestrian detection method based on deep learning, including:

[0051] S100: Obtain a sample data set with a pedestrian target, and preprocess the sample data set;

[0052] S200: Build an SSD pedestrian detection model, and optimize the SSD pedestrian detection model to obtain an optimized SSD pedestrian detection model;

[0053] S300: Send the sample data set obtained through the preprocessing of the ...

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Abstract

The invention discloses a pedestrian detection method based on deep learning, and belongs to the technical field of deep learning and pedestrian detection. The method comprises the following steps: employing ResNet, VoVNet and K-means clustering for optimization based on a conventional SSD pedestrian detection model, solving the problems of missing detection and false detection caused by pedestrian density or shielding and too small pedestrian postures in an SSD algorithm, and improving the detection precision. The accuracy and the real-time performance of pedestrian detection and the small target pedestrian detection performance are improved.

Description

technical field [0001] The present invention relates to the technical field of deep learning and pedestrian detection, and more specifically relates to a pedestrian detection method based on deep learning. Background technique [0002] Pedestrian detection is an important research branch in the field of computer vision. The main task is to determine whether pedestrians appear in the input image or video sequence and determine their location. Pedestrian detection technology is widely used in video surveillance, vehicle assisted driving, intelligent robots and other fields. [0003] At present, with the rapid development of computer vision technology, pedestrian detection, as an important research field, has also made great progress and gradually tends to practical applications. With the research and application of deep learning algorithms in pedestrian detection, a series of deep learning pedestrian detection algorithms have been derived on the basis of convolutional neural ...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/32G06K9/62G06N3/04G06N3/08
CPCG06N3/08G06V20/53G06V10/25G06N3/045G06F18/23213G06F18/214
Inventor 卢立晖索婕王化建张立华司鹏程丁明亮李磊张正强
Owner QUFU NORMAL UNIV
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