Target detection method, target detection model and target detection system based on cascade detector

A target detection and detector technology, applied in the field of computer vision, can solve the problem of low target positioning accuracy

Active Publication Date: 2019-06-14
WUHAN JINGCE ELECTRONICS GRP CO LTD +1
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Problems solved by technology

[0005] Aiming at at least one defect or improvement requirement of the prior art, the present invention provides a cascaded detector-based target detection method, target detection model and system, and performs multiple target bounding boxes on...

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  • Target detection method, target detection model and target detection system based on cascade detector
  • Target detection method, target detection model and target detection system based on cascade detector
  • Target detection method, target detection model and target detection system based on cascade detector

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Embodiment Construction

[0078] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention. In addition, the technical features involved in the various embodiments of the present invention described below can be combined with each other as long as they do not constitute a conflict with each other.

[0079] Below at first explain and illustrate with regard to the technical terms of the present invention:

[0080] Convolutional Neural Network (CNN for short) is a feedforward neural network in which artificial neurons can respond to surrounding units and can perform large-scale image processing. A convolutional neural network consists of convolutional and pooling layers. RCNN (Regions with C...

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Abstract

The invention discloses a target detection method, a target detection model and a target detection system based on a cascade detector. The target detection method comprises the following steps of S1,training the target detection model by adopting a training data set with a target label; S2, inputting a to-be-detected picture into the trained target detection model, and performing feature extraction, upsampling and feature fusion to obtain feature maps P2, P3,..., Pn with different sizes; S3, predicting according to the feature map Pn to obtain a target position Bn and a category Cn; extracting corresponding features from the corresponding feature map Pi-1 according to the target position Bi for target prediction to obtain a target position Bi-1 and a category Ci-1, i = 3-n; S4, taking thetarget position B2 as a final prediction result. According to the invention, through the multiple iterative regression prediction of the the target candidate box, the target position with more accurate prediction is obtained, the target detection precision is improved, and the detection accuracy is higher.

Description

technical field [0001] The invention belongs to the technical field of computer vision, and more specifically relates to a cascaded detector-based high-precision target detection model, target detection system and method. Background technique [0002] In the field of computer vision, target detection is a very active and challenging research direction. Unlike classification tasks, target detection not only needs to identify the category of the target, but also locates the position of the target, so as to achieve the task of positioning and recognition. , It is closely related to many real-life applications, such as the detection and recognition of license plates in the field of traffic security, the detection and recognition of driverless car traffic lights and traffic signal signs, the algorithm of camera face positioning, etc. Target detection is usually divided into two steps: the first step is to locate the target area, and the second step is to identify the content in t...

Claims

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Application Information

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IPC IPC(8): G06K9/62
Inventor 张胜森林宏志郑增强白翔刘荣华沈亚非
Owner WUHAN JINGCE ELECTRONICS GRP CO LTD
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