Bell Labs has developed a
video-conferencing system that enables video streams to be adjusted to
user emotions so as to help maintain audience attention.
During a lecture it can sometimes prove a real
struggle to keep the audience’s attention. This is all the more so when
it comes to a video-conference session where image quality may not be
up to standard for the viewers. Now a team of researchers at
Alcatel-Lucent’s
Bell Labs
has been working on ways of optimising video streams in order to retain
the attention of everyone taking part in a video-conference. The system
that was presented on 20 June at the Bell Labs Open Days held at their
Research Center at Villarceaux, near Paris, uses ‘affective computing’,
i.e. devices and systems that can recognise, interpret and process human
emotions, and applies this information to video-conferencing
technology.
User-centric technology
The system uses two types of device for analysing user behaviour in
order to suit the video stream optimally to an individual viewer. The
first is a camera which uses facial recognition to pick up physical
behaviour. The second is a sensor which measures brain waves and the
user’s state of emotion or stress. “Measuring brain waves is the most
avant-garde aspect of our method,” the researchers pointed out,
underlining that “the system provides fast, efficient feedback on user
attention.” Software based on a ‘hidden Markov model’ then picks up data
stored on a server and aggregates it in order to determine the video
stream which would best attract and hold user attention. In addition,
the person delivering the video-conference can also intervene and
generate video streams by using key words and key gestures.
Towards a new approach to visual streaming
The Bell Labs researchers further explained that: “This optimisation
means that you can relay images which are more in line with what the
users require or expect. The system has a number of potential fields of
application.” The education field was one of the examples they gave.
Online courses using video content could be among the first
beneficiaries of the system, as information coming from the camera and
the brain wave sensor will provide the video-conference lecturer with
instant feedback so that s/he can relay video content which is more
suited to the students’ concentration levels. The system might also be
used for sports event broadcasts, enabling the viewer to enjoy more time
viewing what s/he finds most interesting.
Aucun commentaire:
Enregistrer un commentaire