Max-Planck-Institut für Informatik
max planck institut
mpii logo Minerva of the Max Planck Society

MPI-INF or MPI-SWS or Local Campus Event Calendar

<< Previous Entry Next Entry >> New Event Entry Edit this Entry Login to DB (to update, delete)
What and Who
Title:Marker-less Motion Capture in General Scenes with Sparse Multi-camera Setups
Speaker:Ahmed ELHAYEK
coming from:Max-Planck-Institut für Informatik - D4
Speakers Bio:
Event Type:Promotionskolloquium
Visibility:D1, D2, D3, D4, D5, SWS, RG1, MMCI
We use this to send out email in the morning.
Level:Public Audience
Date, Time and Location
Date:Wednesday, 9 December 2015
Duration:60 Minutes
Building:E1 4
Human motion-capture from videos is one of the fundamental problems in
computer vision and computer graphics. Its applications can be found in
a wide range of industries. Even with all the developments in the past
years, industry and academia alike still rely on complex and expensive
marker-based systems. Many state-of-the-art marker-less motion-capture
methods come close to the performance of marker-based algorithms, but
only when recording in highly controlled studio environments with
exactly synchronized, static and sufficiently many cameras. While
relative to marker-based systems, this yields an easier apparatus with a
reduced setup time, the hurdles towards practical application are still
large and the costs are considerable. By being constrained to a
controlled studio, marker-less methods fail to fully play out their
advantage of being able to capture scenes without actively modifying them.
In the area of marker-less human motion-capture, this thesis proposes
several novel algorithms for simplifying the motion-capture to be
applicable in new general outdoor scenes. The first is an optical
multi-video synchronization method which achieves subframe accuracy in
general scenes. In this step, the synchronization parameters of multiple
videos are estimated. Then, we propose a spatio-temporal motion-capture
method which uses the synchronization parameters for accurate
motion-capture with unsynchronized cameras. Afterwards, we propose a
motion capture method that works with moving cameras, where multiple
people are tracked even in front of cluttered and dynamic backgrounds
with potentially moving cameras. Finally, we reduce the number of
cameras employed by proposing a novel motion-capture method which uses
as few as two cameras to capture high-quality motion in general
environments, even outdoors. The methods proposed in this thesis can be
adopted in many practical applications to achieve similar performance as
complex motion-capture studios with a few consumer-grade cameras, such
as mobile phones or GoPros, even for uncontrolled outdoor scenes.
Name(s):Ellen Fries
EMail:--email address not disclosed on the web
Video Broadcast
Video Broadcast:NoTo Location:
Tags, Category, Keywords and additional notes
Attachments, File(s):
  • Ellen Fries, 12/02/2015 11:06 AM -- Created document.