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Garment positioning and detecting method based on depth convolution nerve network

A neural network and deep convolution technology, applied in the field of clothing location detection based on deep convolutional neural network, can solve problems such as constraint accuracy, improper selection of feature extraction methods, and poor timeliness

Inactive Publication Date: 2015-07-15
CHONGQING INST OF GREEN & INTELLIGENT TECH CHINESE ACADEMY OF SCI
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Problems solved by technology

The deep neural network generally has the problem of poor timeliness due to the large number of ROI regions to be detected, and the improper selection of feature extraction methods, which greatly restricts the accuracy. solution

Method used

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  • Garment positioning and detecting method based on depth convolution nerve network
  • Garment positioning and detecting method based on depth convolution nerve network
  • Garment positioning and detecting method based on depth convolution nerve network

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Embodiment Construction

[0076] The preferred embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0077] The invention provides a clothing location detection method based on a deep convolutional neural network, such as figure 1 As shown, the method includes the following steps:

[0078] Step 1: In the input image, select the ROI of the area to be detected;

[0079] The spacing within the defined area is,

[0080] In ( R ) = max e ∈ E ω ( e ) ,

[0081] That is, the weight value of the edge with the largest weight in the region; among them, ω(e) represents the weight between two adjacent points, and E represents all the edges in the region;

[0082] Define the spacing between regions as follows:

[0083] ...

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Abstract

The invention relates to a garment positioning and detecting method based on a depth convolution nerve network, and belongs to the technical field of image processing and computer vision analyzing. The method comprises the steps that firstly, an area ROI to be detected is reasonably selected in an input image; secondly, feature extraction is performed on the area to be detected by utilizing the depth convolution nerve network; lastly, all feature vectors are judged by adopting an LibSVM classifier. According to the garment positioning and detecting method based on the depth convolution nerve network, a garment in the image to be detected can be detected and accurately positioned, and intelligent garment trying and changing can be achieved.

Description

technical field [0001] The invention belongs to the technical fields of image processing and computer vision analysis, and relates to a clothing location detection method based on a deep convolutional neural network. Background technique [0002] The clothing detection system has become an emerging application direction in the field of image processing and computer vision analysis. The research on clothing detection is a key technology of intelligent image design. This technology detects the clothing in the image to be detected and gives precise positioning tips. It can realize intelligent fitting and changing of clothes, which has huge market application value and social significance. [0003] At this stage, many countries at home and abroad have carried out research on deep learning neural networks, but there are few examples of applying this technology to the field of clothing detection. The deep neural network generally has the problem of poor timeliness due to the larg...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06K9/46
Inventor 程诚颜卓李远钱覃勋辉周祥东周曦袁家虎
Owner CHONGQING INST OF GREEN & INTELLIGENT TECH CHINESE ACADEMY OF SCI
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