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Target detection method, device and storage medium

A detection method and target technology, applied in character and pattern recognition, instruments, computer components, etc., can solve the problems of increased detection difficulty and low accuracy, and achieve the effect of reducing detection difficulty and improving accuracy

Active Publication Date: 2018-08-10
ZEBRED NETWORK TECH CO LTD
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  • Application Information

AI Technical Summary

Problems solved by technology

[0004] Due to the various deformations of pedestrians and other targets, in order to improve the detection accuracy when using the above methods for detection, it is necessary to expand the amount of data to include enough samples, and at the same time, it is necessary to increase the capacity of the model to cover possible deformations. Not only will it increase the difficulty of detection, but the accuracy of detection is not high

Method used

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  • Target detection method, device and storage medium
  • Target detection method, device and storage medium
  • Target detection method, device and storage medium

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Embodiment Construction

[0069] 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.

[0070] The target detection method provided by the embodiment of the present invention can be applied to the detection scene of the target object in the image, especially to the non-rigid target detection scene where the posture of the target itself changes or various deformations occur. At present, the detection of non-rigid targets such as pedestrians is mainly based on single-frame images in video streams, using traditional feature extraction and classificat...

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Abstract

The invention provides a target detection method, device and a storage medium. The method comprises steps: a to-be-detected target in a current frame image in video data is obtained through initial detection; the to-be-detected target and at least one target in a former frame image of the current frame image are matched; and if a target matched with the to-be-detected target exists in the former frame image, the category and the position information of the to-be-detected target are determined according to a feature layer of the to-be-detected target in the current frame image and the feature layer in former m frame images of the current frame image, wherein m is a positive integer. According to the target detection method, the device and the storage medium provided in the invention, the detection difficulty can be reduced, and the detection accuracy can also be improved.

Description

technical field [0001] The present invention relates to image detection technology, in particular to a target detection method, device and storage medium. Background technique [0002] The precision requirements for the detection of vehicles, pedestrians and other objects in the assisted driving of automobiles are very strict. The current detection technology is relatively accurate for rigid objects such as vehicles, traffic signs, and lane lines, while the detection accuracy for non-rigid objects such as pedestrians or bicycles is relatively low. [0003] At present, detection methods for pedestrians are mainly based on single-frame images in video streams, using traditional feature extraction and classification methods, or detection based on deep learning methods such as convolutional neural networks. Among them, the traditional method of feature extraction and classification is mainly to design the characteristics of pedestrians in advance, and then use machine learning ...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06K9/32G06K9/62
CPCG06V20/48G06V20/40G06V20/46G06V10/25G06V2201/07G06F18/22G06F18/2431
Inventor 李朝辉吴颖谦蒋宗杰张燕昆
Owner ZEBRED NETWORK TECH CO LTD
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