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Conveying conversational cues through video.
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Conveying conversational cues through video.
作者:
Chen, Milton Robert.
面頁冊數:
87 p.
附註:
Advisers: Pat Hanrahan; Terry Winograd.
附註:
Source: Dissertation Abstracts International, Volume: 64-05, Section: B, page: 2261.
Contained By:
Dissertation Abstracts International64-05B.
標題:
Computer Science.
電子資源:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3090568
ISBN:
049638290X
Conveying conversational cues through video.
Chen, Milton Robert.
Conveying conversational cues through video.
[electronic resource] - 87 p.
Advisers: Pat Hanrahan; Terry Winograd.
Thesis (Ph.D.)--Stanford University, 2003.
In this dissertation, we describe empirical findings and novel algorithms for conveying floor control hand gestures, lip movements, and eye contact over the video medium. We describe (1) a variable frame rate streaming algorithm based on our finding that the average video frame rate can be reduced to one frame every few seconds and still allow effective floor control if hand movements are transmitted without delay; (2) a low latency lip synchronization algorithm based on our finding that audio can temporarily lead video and still be perceived as synchronized if the audio and video are brought into synchrony within a short period; and (3) an eye contact algorithm based on our finding that the sensitivity to eye contact is asymmetric, in that we are less sensitive to eye contact when people look below our eyes than when they look to the left, right, or above our eyes.
ISBN: 049638290XSubjects--Topical Terms:
212513
Computer Science.
Conveying conversational cues through video.
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In this dissertation, we describe empirical findings and novel algorithms for conveying floor control hand gestures, lip movements, and eye contact over the video medium. We describe (1) a variable frame rate streaming algorithm based on our finding that the average video frame rate can be reduced to one frame every few seconds and still allow effective floor control if hand movements are transmitted without delay; (2) a low latency lip synchronization algorithm based on our finding that audio can temporarily lead video and still be perceived as synchronized if the audio and video are brought into synchrony within a short period; and (3) an eye contact algorithm based on our finding that the sensitivity to eye contact is asymmetric, in that we are less sensitive to eye contact when people look below our eyes than when they look to the left, right, or above our eyes.
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Visual conversational cues such as hand gestures, lip movements, and eye contact can be conveyed through a video medium. However, existing videoconferencing systems often subtly distort these conversational cues such that the person, rather than the medium, is viewed with negative attributes. For example, a delayed response due to video transmission may cause the person to be viewed as slow. Lip movements not synchronized with speech due to video compression may cause the person to be viewed as less credible. And difficulties with eye contact due to camera placement may cause the person to be viewed as unfriendly.
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We implemented our algorithms in a scalable software-based visual communication system called the Video Auditorium. The implementation of Video Auditorium is motivated by our 6-month classroom observational study of Stanford Online that found that when the instructor cannot see the remote students, there is essentially no interaction with them. We used Video Auditorium to visually connect students in Germany, Sweden, Slovenia, and Berkeley with Stanford in a 4-month pilot class, and found that when the instructor can see the remote students, the remote interaction is as rich and rewarding as the interaction with the local students.
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