Dr. Fabio Poiesi presents Formations of flying cameras to follow and film a moving target
On 2016-03-07 16:00:00 at KN:E-112, Karlovo náměstí 13, Praha 2
Quadcopters are highly manoeuvrable and can provide an effective means for an
agile positioning of sensors such as cameras (flying cameras). In this talk I
will present how visual sensing can allow flying cameras to fly in formations
without the need of external positioning systems such as GPS. I will address the
problem of formations following a moving (ground) target, and explain a
distributed decision-making process performed via sensing and sharing of
information among neighbouring flying cameras. Given formations of up to 12
flying cameras, I will show how the target-following performance varies when the
visual sensing is used as opposed to a GPS-only-based positioning.
Short bio: Fabio Poiesi is a postdoc in the Centre for Intelligent Sensing at
Queen Mary University of London, UK. He received his PhD degree from the same
university in March 2014, supervised by Prof. Andrea Cavallaro. His research
interests involve multi-object tracking, motion analysis and visual systems for
the autonomous control of flying robots. He published in journals such as IEEE
Trans. on Image Processing, IEEE Trans. on Circuits and Systems for Video
Technology, Computer Vision and Image Understanding, and in conferences such as
IROS, ICIP and AVSS. He is currently working under the European Project COPCAMS
(copcams.eu).
agile positioning of sensors such as cameras (flying cameras). In this talk I
will present how visual sensing can allow flying cameras to fly in formations
without the need of external positioning systems such as GPS. I will address the
problem of formations following a moving (ground) target, and explain a
distributed decision-making process performed via sensing and sharing of
information among neighbouring flying cameras. Given formations of up to 12
flying cameras, I will show how the target-following performance varies when the
visual sensing is used as opposed to a GPS-only-based positioning.
Short bio: Fabio Poiesi is a postdoc in the Centre for Intelligent Sensing at
Queen Mary University of London, UK. He received his PhD degree from the same
university in March 2014, supervised by Prof. Andrea Cavallaro. His research
interests involve multi-object tracking, motion analysis and visual systems for
the autonomous control of flying robots. He published in journals such as IEEE
Trans. on Image Processing, IEEE Trans. on Circuits and Systems for Video
Technology, Computer Vision and Image Understanding, and in conferences such as
IROS, ICIP and AVSS. He is currently working under the European Project COPCAMS
(copcams.eu).