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Target detection system and method

A target detection and target object technology, which is applied in the direction of instruments, character and pattern recognition, computer components, etc., can solve the problems of target detection technology detection efficiency and detection accuracy that fail to meet the actual requirements, and achieve the effect of improving detection efficiency

Active Publication Date: 2015-09-23
北京科富兴科技有限公司
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  • Description
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  • Application Information

AI Technical Summary

Problems solved by technology

[0004] In order to solve the technical problem that the detection efficiency and detection accuracy of the existing target detection technology fail to meet the actual requirements, the embodiment of the present invention provides a target detection system and method

Method used

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Embodiment 1

[0032] An embodiment of the present invention provides a target detection method, such as figure 1 As shown, it mainly includes the following steps:

[0033] Step 101, obtaining the feature map and double-resolution feature map of the input image;

[0034] Step 102, the root filter of the deformable part model acts on the feature map to capture the global features of the target object, and each component filter of the deformable part model acts on the feature map with twice the resolution to capture Take the local features of the target object;

[0035] Step 103, a plurality of SVM classifiers trained based on the EM algorithm identify the target object in the input image according to the global features and local features of the target object;

[0036] Among them, in the field of machine learning, a support vector machine (SVM, Support Vector Machine) is a supervised learning model, which is usually used for pattern recognition, classification, and regression analysis.

[...

Embodiment 2

[0040] An embodiment of the present invention provides a target detection system, such as figure 2 As shown, the system includes:

[0041] A feature map unit 21, which acquires a feature map and a double-resolution feature map of the input image;

[0042] The deformable component model unit 22 includes a root filter and a plurality of component filters, the root filter is used to act on the feature map to capture the global features of the target object, each of the component filters is used to act on Grab the local features of the target object on the feature map with twice the resolution;

[0043] The classifier unit 23 includes a plurality of SVM classifiers trained based on the EM algorithm, configured to identify the target object in the input image according to the global features and local features of the target object, and output a detection result.

[0044] The target detection system of the embodiment of the present invention can be applied to the statistical item...

Embodiment 3

[0046] This embodiment describes in detail the specific implementation of the object detection method and system of the embodiment of the present invention.

[0047] The object detection method and system of the embodiment of the present invention are mainly based on technologies such as weighted deformable part model and EM training hybrid SVM, and have achieved good results in the detection of similar objects such as pedestrians and vehicles.

[0048] Among them, the deformable part model is a star model composed of a root filter and several part filters. The deformable part model takes into account the overall information of the target and the appearance information of each part and its spatial relationship, and can be extracted to More informative than holistic-based approaches.

[0049] The main features of this deformable part model are as follows:

[0050] (1) The feature description ability of the combination of global and local. The root filter is a global template f...

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Abstract

The invention discloses a target detection method. The method comprises the steps of acquiring a feature graph and a double resolution feature graph of an input image; a root filter of a deformable part model acting on the feature graph and capturing a global feature of a target object, and all part filters of the deformable part model acting on the double resolution feature graph and capturing a local feature of the target object; a plurality of support vector machine (SVM) classifiers based on expectation maximization (EM) algorithm training identify the target object in the input image according to the global feature and local feature of the target object; and a detection result is output. Correspondingly, the invention also discloses a target detection system. The detection precision and performance of the system can meet actual requirements, and furthermore, large scale industrial application of the system is expected to realize in a short term.

Description

technical field [0001] The invention relates to the technical field of target detection, in particular to a target detection system and method. Background technique [0002] At present, there are many academic models for target detection. Among them, the Deformable Part Model (DPM) is the most popular object detection model in graphics recently. It is popular because it can accurately detect targets and is recognized as the best. Object detection algorithm. [0003] However, when the target detection technology using DPM is applied to the detection of vehicles and pedestrians, the detection effect still needs to be improved. The detection efficiency and detection accuracy of the existing target detection technology not only fail to meet the actual requirements, but also are difficult to be applied in large-scale industrialization. Contents of the invention [0004] In order to solve the technical problem that the detection efficiency and detection accuracy of the existin...

Claims

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Application Information

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IPC IPC(8): G06K9/62
CPCG06V2201/08G06V2201/07G06F18/2411
Inventor 华宝洪汪蒲阳扈戈洋高斌陈俊宇
Owner 北京科富兴科技有限公司
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