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Title:
SIGNIFICANCE TESTING METHOD FOR 3D IMAGE
Document Type and Number:
WIPO Patent Application WO/2018/023734
Kind Code:
A1
Abstract:
Disclosed is a significance testing method for a 3D image, comprising steps of: (1) respectively extracting depth characteristic vectors of a color image and a depth image on the basis of a convolutional neural network; (2) respectively generating significance maps of the depth image and the color image according to a three-layer neural network and the extracted depth characteristic vectors of the color image and the depth image; (3) linearly blending the significance maps of the color image and the depth image to obtain a significance map of a 3D image. According to the present invention, depth study characteristics of a color image and a depth image are extracted in a multi-scale area on the basis of a CNN model; a significance map of the depth image (or the color image) is generated using a trained NN model on the basis of a depth characteristic vector and a significance label of the area, the NN model being used as a classifier in this case; with the depth significance map and a color significance map as an input, a final significance map of a 3D image is generated using a linear blending method. The present testing method has advantages of small error and high precision.

Inventors:
WANG, Xu (Nanhai Ave. 3688, NanshanShenzhen, Guangdong 0, 518060, CN)
ZHANG, Qiudan (Nanhai Ave. 3688, NanshanShenzhen, Guangdong 0, 518060, CN)
JIANG, Jianmin (Nanhai Ave. 3688, NanshanShenzhen, Guangdong 0, 518060, CN)
LAI, Zhihui (Nanhai Ave. 3688, NanshanShenzhen, Guangdong 0, 518000, CN)
Application Number:
CN2016/093637
Publication Date:
February 08, 2018
Filing Date:
August 05, 2016
Export Citation:
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Assignee:
SHENZHEN UNIVERSITY (Nanhai Ave. 3688, NanshanShenzhen, Guangdong 0, 518060, CN)
International Classes:
G06K9/46
Attorney, Agent or Firm:
HENSEN INTELLECTUAL PROPERTY FIRM (10H Shangbu Building, No.68 Nanyuan Road Futia, Shenzhen Guangdong 0, 518000, CN)
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