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A machine learning-based scanning path prediction method and device

A technology of machine learning and prediction methods, applied in the field of image processing, can solve the problems of predicting fixation points relying on static saliency maps, insufficient predicting saccade paths, etc., achieving good universality and scalability, and eliminating dependencies.

Active Publication Date: 2022-05-06
XIDIAN UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The embodiment of the present invention provides a machine learning-based glance path prediction method and device, which solves the problem in the prior art that the gaze point prediction is too dependent on the static saliency map, and the technical problem that the glance path prediction in natural scene pictures is insufficient , to eliminate the dependence of the model on the saliency map, and take into account the timing between gaze points, and achieve good technical results on multiple public data sets

Method used

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  • A machine learning-based scanning path prediction method and device
  • A machine learning-based scanning path prediction method and device
  • A machine learning-based scanning path prediction method and device

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Experimental program
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Embodiment 1

[0059] figure 1 It is a schematic flow chart of a method for predicting a glance path based on machine learning in an embodiment of the present invention. Such as figure 1 As shown, the method includes:

[0060] Step 110: Obtain an image data set to be processed, wherein each image information in the image data set has corresponding truth value information;

[0061] Specifically, the image data set to be processed refers to a collection of multiple pictures waiting to be processed, and the corresponding ground truth information refers to the gaze point coordinates of the corresponding image as a label.

[0062] Step 120: making training samples of the image data set according to the true value information;

[0063] Further, the making the training samples of the image data set according to the true value information specifically includes: processing the true value information to obtain eye movement data information of N observers; The observer's eye movement data is subjec...

Embodiment 2

[0092] The effects of the present invention will be further described below in conjunction with simulation experiments.

[0093] 1. Simulation conditions:

[0094] In the simulation experiment of the present invention, the computer system used is Ubuntu 16.04, the machine learning framework is TensorFlow, the version is 1.1.0, the Python version used is 2.7, and the vector of the embedded matrix is ​​V×M, and V is made according to different data sets. Corresponding adjustments, M takes 512, and C takes 16, indicating 8 fixation points.

[0095] 2. Simulation content:

[0096] In the simulation experiment of the present invention, picture names and Arabic numerals are mapped to form a dictionary, an experiment is designed for each data set, training set pictures and test set pictures are selected according to numbers, and corresponding eye movement data sets are processed to obtain labels. Use the samples to train the LSTM network, use the gradient descent optimization algor...

Embodiment 3

[0101] Based on the same inventive concept as a machine learning-based glance path prediction method in the foregoing embodiments, the present invention also provides a machine learning-based glance path prediction device, such as image 3 shown, including:

[0102] A first obtaining unit, the first obtaining unit is used to obtain an image data set to be processed, wherein each image information in the image data set has corresponding truth value information;

[0103] a first production unit, the first production unit is configured to produce training samples of the image data set according to the truth information;

[0104] a second obtaining unit, the second obtaining unit is configured to obtain image feature representation information of the image information according to the image information;

[0105] A first construction unit, the first construction unit is used to construct and train an LSTM network according to the image feature representation information and the ey...

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Abstract

The present invention provides a machine learning-based scanning path prediction method and device, which relate to the field of computer technology. The method includes: obtaining an image data set to be processed, wherein each image information in the image data set has a corresponding value information; according to the true value information, make a training sample of the image data set; according to the image information, obtain the image feature representation information of the image information; according to the image feature representation information and the eye movement data samples, construct and train an LSTM network; predict a scan path according to the LSTM network. It solves the problem that the prediction of fixation points in the prior art relies too much on static saliency maps, and the technical problem of insufficient prediction of glance paths in natural scene pictures, achieves the elimination of the model's dependence on saliency maps, and takes into account the gap between gaze points. The timing of the algorithm has achieved good technical results on multiple public data sets.

Description

technical field [0001] The present invention relates to the technical field of image processing, in particular to a machine learning-based scanning path prediction method and device. Background technique [0002] With the rapid development of information technology, human beings have entered an era of large-scale data growth. Digital images and videos have become important carriers of information. Massive image data is an important part of obtaining information. How to effectively select the most Valuable information has gradually become a hot spot in the field of image processing. [0003] In the prior art, the problem of predicting the fixation point is too dependent on the static saliency map. At the same time, the prior art also has many deficiencies in predicting the path of the glance in the natural scene picture. Contents of the invention [0004] The embodiment of the present invention provides a machine learning-based glance path prediction method and device, whi...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06V10/82G06N3/04G06N3/08
CPCG06T7/0002G06T2207/20081G06T2207/20084
Inventor 齐飞高帅石光明夏朝辉
Owner XIDIAN UNIV