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Target detection method and device

A technology for target detection and images to be detected, which is applied in image analysis, instruments, calculations, etc., and can solve the problem of low accuracy of multi-target detection

Inactive Publication Date: 2015-04-22
CHINA SECURITY & FIRE TECH GRP +1
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  • Description
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Problems solved by technology

[0003] Embodiments of the present invention provide a target detection method and device to solve the problem of low multi-target detection accuracy in existing pedestrian detection methods

Method used

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  • Target detection method and device

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Embodiment Construction

[0046] In the embodiment of the present invention, the deep learning model and the classifier are combined to be used in target detection, and the feature vector of the image to be detected is used as the input data of the deep learning model, and then the state value of the hidden layer node of the deep learning model is obtained, and finally The state value of the last layer of hidden layer nodes is used as the input of the classifier to obtain the classification result, which can accurately determine the target contained in the image to be detected and the number of contained targets. Further, in the embodiment of the present invention, some or all of the directional gradient histogram feature vector, geometric shape feature vector and color self-similar feature vector are used as the feature vectors of the trained input deep learning model, and these feature vectors extract the target The low-level features and mid-level features in the deep learning model are trained and l...

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Abstract

The embodiment of the invention provides a target detection method and device. The target detection method and device are used for solving the problem that according to an existing pedestrian detecting method, the detection precision is low when multiple targets are detected. The target detection method comprises the steps that at least one type of feather vectors of an image to be detected are determined, the determined feature vectors are input into a trained deep learning model so that the state values of hidden nodes of the deep learning model can be obtained, the state value of the last hidden node of the deep learning model is input into a classifier, and the number of targets contained in the image to be detected is determined according to an output result of the classifier.

Description

technical field [0001] The present invention relates to the technical field of image and video processing, in particular to a target detection method and device. Background technique [0002] At present, mainstream pedestrian detection methods mostly use frame difference, background difference, optical flow field calculation, background modeling and neural network learning to distinguish background and pedestrians, so as to achieve the purpose of detecting and tracking pedestrians. However, since moving objects such as pedestrians are easily affected by illumination changes, poses, shadows, and occlusions, the correct recognition rate of these methods is greatly reduced. In addition, the detection accuracy of existing methods for multiple pedestrian targets under complex background conditions is also low, which cannot fully meet the new requirements of the current security monitoring and intelligent transportation fields. Contents of the invention [0003] Embodiments of ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00
CPCG06F18/2411
Inventor 贾惠柱陈瑞解晓东文湘鄂
Owner CHINA SECURITY & FIRE TECH GRP
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