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A Human Eye Gaze Estimation Method Based on Quantized Minimal Residual Entropy Criterion

A fixation point and residual entropy technology, applied in the field of fixation point estimation in human-computer interaction, can solve problems such as slow estimation speed and strong scene dependence, achieve low hardware requirements, improve estimation accuracy, and ensure similarity effects

Active Publication Date: 2019-09-20
XI AN JIAOTONG UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

For example: the estimation accuracy still needs to be improved, the dependence on the scene is strong, and the estimation speed is relatively slow, etc.

Method used

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  • A Human Eye Gaze Estimation Method Based on Quantized Minimal Residual Entropy Criterion
  • A Human Eye Gaze Estimation Method Based on Quantized Minimal Residual Entropy Criterion
  • A Human Eye Gaze Estimation Method Based on Quantized Minimal Residual Entropy Criterion

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Embodiment Construction

[0044] The present invention will be further described below in conjunction with the accompanying drawings.

[0045] The flow chart of the concrete implementation of the present invention is as figure 1 As shown, the steps involved are as follows:

[0046] Step 1: face image extraction;

[0047] Step 2: Accurate extraction and alignment of human eye images;

[0048] Step 3: Human eye feature extraction and dimensionality reduction;

[0049] Step 4: Estimation of the gaze point of the human eye.

[0050] The specific implementation steps of step 1 are:

[0051] The AdaBoost algorithm is used to locate the face of the collected image, and then the face image is extracted to provide the basis for subsequent processing.

[0052] The specific implementation steps of step 2 are:

[0053] After the face image is extracted in step 1, the human eyes are accurately extracted and aligned using sub-pixel edge detection and affine transformation. The specific method is:

[0054] Fi...

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Abstract

The invention discloses a human eye gaze point estimation method based on the quantitative minimum residual entropy criterion, which belongs to the field of machine vision and mainly includes the following steps: 1. Human face image extraction; 2. Human eye image precise extraction and alignment; 3. Human eye feature extraction and dimensionality reduction; 4. Human eye fixation point position estimation; the method of the present invention can greatly shorten the estimation time while ensuring the estimation accuracy under different environments, thereby ensuring the timeliness of the estimation process.

Description

technical field [0001] The invention relates to the gaze point estimation field of human-computer interaction, in particular to a human eye gaze point estimation method based on the quantitative minimum residual entropy criterion. Background technique [0002] With the development of the times, human eye gaze estimation technology has been widely used in real life, and it has become an important research object in many fields. At present, human eye foveation technology has been widely used in a variety of disciplines, including cognitive science, psychology (especially psycholinguistics, paradigms of the visual world, Human–Computer Interaction (HCI). ), market research and medical research (neurodiagnosis), etc. [0003] Although the human gaze point estimation technology has been widely used, it still faces many problems. For example, the estimation accuracy still needs to be improved, the dependence on the scene is strong, and the estimation speed is relatively slow, et...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/00G06K9/62
CPCG06V40/171G06F18/214
Inventor 张雪涛杨奔陈霸东姜沛林王飞
Owner XI AN JIAOTONG UNIV