A dual-mode deep learning descriptor construction method based on graphic primitives

A technology of deep learning and graphics primitives, applied in image analysis, image data processing, character and pattern recognition, etc., can solve problems such as the large amount of calculation of classic descriptors and the difficulty of applying real-time systems

Active Publication Date: 2019-03-01
ANHUI NORMAL UNIV
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Problems solved by technology

[0003] The embodiment of the present invention provides a method for constructing a dual-mode deep learning descriptor based on image primitives, which aims to solve the problem that the classic descriptor has a large amount of calculation and is difficult to apply to a real-time system

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  • A dual-mode deep learning descriptor construction method based on graphic primitives
  • A dual-mode deep learning descriptor construction method based on graphic primitives

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Embodiment Construction

[0039] 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.

[0040] The present invention respectively learns the attribute category of the patch image by labeling samples, uses the graphic primitive to learn the geometric feature of the patch image, and fuses the attribute category and the geometric feature to obtain the feature vector of the local patch image, that is, the descriptor based on the graphic primitive . The registration between patches is completed by the similarity of descriptor vectors, and the classification and description based on machine learning descriptors is realized.

[0041] figure 1 A schematic flow chart of the image primitive-b...

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Abstract

The method is suitable for the technical field of image registration. The invention provides a dual-mode deep learning descriptor construction method based on graphic primitives. According to the method, attribute categories of patch images are learned by labeling samples, geometric features of the patch images are learned by utilizing graphic primitives, and the attribute categories and the geometric features are fused to obtain feature vectors of local patch images, namely descriptors based on the graphic primitives. Registration between the patches is completed by describing similarity of the sub-vectors. According to the dual-mode deep learning descriptor construction method based on the graphic primitives, which is provided by the invention, a descriptor classification method calculated by a GPU (Graphics Processing Unit) is explored aiming at the defect that a classic image registration method is relatively large in CPU (Central Processing Unit) calculation amount. A descriptor training set is mainly established, a multi-mode convolutional network is constructed, categories and geometric modes are trained on a GPU, and classification and registration of local patch images areachieved. The classification description method of the descriptors and the implementation problem on the GPU are solved.

Description

technical field [0001] The invention belongs to the technical field of image registration, and provides a method for constructing a dual-mode deep learning descriptor based on image primitives. Background technique [0002] Feature matching is the mainstream method of image registration. The classic image registration method uses local feature descriptors, which take the local area of ​​the image centered on the key point as the object, and describe the features of the area according to the grayscale information of its internal pixels. , and a feature vector expressing the local information around the key points of the image is obtained. However, classical descriptors are computationally intensive and difficult to apply to real-time systems, and are not suitable for mobile devices. Contents of the invention [0003] An embodiment of the present invention provides a method for constructing a dual-mode deep learning descriptor based on an image primitive, which aims to solv...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/46G06K9/62G06T7/13G06T7/30
CPCG06T7/13G06T7/30G06V10/462G06F18/214
Inventor 丁新涛左开中汪金宝接标俞庆英
Owner ANHUI NORMAL UNIV
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