Wearable eye tracker first perspective video image analysis method

A technology of video image and analysis method, which is applied in the direction of instruments, character and pattern recognition, computer parts, etc., can solve the problems of high labor cost and long time consumption, achieve accurate superpixel segmentation, extend the scope of application, and save human resources Effect

Inactive Publication Date: 2016-09-28
SYSU CMU SHUNDE INT JOINT RES INST +1
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Problems solved by technology

However, in a real scene, when wearing a wearable eye tracker, the target area that the subject pays attention to changes in real time and cannot be predicted, so it is impossible to pre-define the area of ​​interest. To furt...

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  • Wearable eye tracker first perspective video image analysis method
  • Wearable eye tracker first perspective video image analysis method
  • Wearable eye tracker first perspective video image analysis method

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Embodiment Construction

[0039] The present invention will be further explained below in conjunction with the accompanying drawings. The accompanying drawings are for illustrative purposes only, and cannot be construed as limiting the present invention; in order to better illustrate this embodiment, some parts in the accompanying drawings will be omitted, enlarged or reduced; for those skilled in the art, certain parts in the accompanying drawings It is understandable that some well-known structures and descriptions thereof may be omitted.

[0040] Such as figure 1 A first-view video image analysis method for a wearable eye tracker is shown, including data preprocessing and data analysis, and the data preprocessing draws a relationship diagram between eye focus point coordinates (x, y) and video image frames, And screen out the video image frame corresponding to the jump point; the data analysis analyzes the first-view video image data through data preprocessing; the specific steps of the data analys...

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Abstract

The invention relates to a wearable eye tracker first perspective video image analysis method. The method comprises steps of data preprocessing in which a relation graph between eye focus point coordinates and first perspective video image frames is drawn, video image frames corresponding to hopping points are found out, and video image frames corresponding to hopping points are screened out in original data of the first perspective video image frames and data analysis in which analysis is carried out according to the preprocessed first perspective video image frames. The data analysis step comprises specific steps: S1, camera calibration is carried out, and the first perspective video image is corrected; S2, image segmentation is carried out, and a target area on which the tested in the image focuses is detected and extracted; and S3, object recognition is carried out, and the target area is effectively recognized. The target area on which the tested focuses can be effectively detected and recognized, and the focus point position is automatically marked.

Description

technical field [0001] The content of the present invention belongs to the field of eye tracker data analysis, and more specifically, it is a first-view video image analysis method of a wearable eye tracker. Background technique [0002] With the development of eye-tracking technology, the development of eye-tracking instrument is becoming more and more mature, and it has good application prospects in various aspects such as psychology, medicine, usability testing, and market research. However, the analysis of eye movement data is mostly focused on the extraction and processing of fixation duration, number of fixation points, areas of interest, and gaze trajectory maps. Currently, the analysis of eye movement data is based on the existing The data analysis module usually mainly obtains visualization results such as heat maps and scanning paths. And its eye movement analysis is mainly aimed at the desktop eye tracker. The desktop eye tracker collects the eye movement data wh...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06K9/62
CPCG06V20/20G06F18/23213
Inventor 李明刘静
Owner SYSU CMU SHUNDE INT JOINT RES INST
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