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Network video individuation search method based on eyeball tracking

A network video, eye tracking technology, applied in the field of computer search, can solve disputes and other problems

Inactive Publication Date: 2009-03-11
ZHEJIANG UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Although it has been mentioned more and more in recent research, it is still debated whether it can really reflect user intent

Method used

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  • Network video individuation search method based on eyeball tracking
  • Network video individuation search method based on eyeball tracking
  • Network video individuation search method based on eyeball tracking

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Experimental program
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Embodiment

[0091] The flow structure of the online video personalized search method based on eye tracking of the present invention is as follows: figure 1 shown. The personalized sorting system includes a client and a server. The client 20 and the eye tracking device are used to obtain the user's attention time 20, and a custom browser is used to obtain the user's attention time. The server includes 30, a sample collection module, and 40. , attention time correction, 50, user database and 60, video database, 70, query interface, 80, traditional engine module, 90, video preprocessing module, 100, video comparison module, 110, attention time prediction module, 120, sorting module .

[0092] The eye tracking device 20 uses an advanced eye movement capture instrument to analyze the video or its summary of the current position of the user's sight. In this example, the eye tracking device uses a common camera (LogitechQuickcam Notebook Pro) with an open source eye tracking system opengazer (...

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Abstract

The invention discloses a network video individualized searching method based on eyeball tracking, which comprises the following steps: 1) sample information of network video concerned time of a user is obtained by the use of an eyeball tracking device; 2) a user concerned time sample obtained is corrected; 3) an appropriate image similarity algorithm is dynamically selected by the application of a decision tree for an unknown network video; 4) the user concerned time of each key frame in the unknown network video is predicted based on the image similarity; 5) the user concerned time of the video is calculated by the concerned time of each key frame in the video for the unknown network video; and 6) individualized network video searching results are generated by the use of the user concerned time and by the combination of traditional searching technology. The network video individualized searching method based on eyeball tracking effectively obtains individual reading interest of the user through the eyeball tracking device and combines the favorite of the user with the network video searching process, thus rendering the final video searching ranking results to be closer to the ideal ranking expected by the user.

Description

technical field [0001] The invention relates to the field of computer search, in particular to an eye-tracking-based network video personalized search method. Background technique [0002] Existing personalization engines rely on user feedback, which can be divided into explicit feedback and implicit feedback. We can derive user preferences from both types of feedback (Salton & Buckley 1990; White, Jose, & Ruthven 2001; White, Ruthven, & Jose 2002). However, users are generally reluctant to provide explicit feedback, so more and more researches now turn to implicit feedback (Granka, Joachims, & Gay 2004; Guan & Cutrell 2007; Fu 2007). Studies have shown that implicit feedback can reflect users' search intentions well (Fox et al. 2005; Dou, Song, & Wen 2007; Fu 2007). And user preferences obtained from a large number of implicit feedbacks are often better than explicit feedbacks. Feedback is more reliable. [0003] Query history: In modern research, the most used implicit ...

Claims

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Application Information

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IPC IPC(8): G06F17/30
Inventor 徐颂华江浩刘智满潘云鹤
Owner ZHEJIANG UNIV
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