PhD Studentship: Advanced Pedestrian Recognition

The   Machine   Perception   Department  of  DaimlerChrysler  R&D  in  Ulm,
south-Germany,  has currently an opening for a Ph.D. student in the area of
computer  vision.  The  open  position concerns our ongoing research on the
challenging   (but  very  interesting)  topic  of  vision-based  pedestrian
detection  from  a  moving  vehicle.  Pedestrians  are  arguably  the  most
vulnerable  traffic participants; more than 6000 pedestrians are killed and
150.000 injured yearly in the EU. Especially children are at risk.

A  number  of  separate  vision modules have been developed in our group to
handle   this   problem:   stereo-   and  radar-based  obstacle  detection,
optical-flow  based  detection of independently moving objects, shape-based
object  detection, intensity-based pattern classification and tracking.  So
far,  these  modules have only been partially combined, and mostly in loose
and  rather  ad-hoc  fashion.  The primary focus of the Ph.D. research lies
therefore  in  how  to better integrate these modules in a high-performance
multi-cue  object detection system, using sound probabilistic principles. A
secondary focus of the Ph.D. research is the pattern classification module.
Here  we  are  interested in automatic and interactive techniques to sample
new  training  data  in  order  to  improve  classifier performance (active
learning).  Experiments  are to be performed both off-line, on unique large
and  prorietary  data sets, and on-line, on-board our Mercedes-Benz vehicle
demonstrator, on the test track and in real urban traffic.

Prospective  applicants should demonstrate an above-average academic record
and  a  solid  background  in  applied  mathematics  and  computer science.
Experience  in  computer vision and pattern recognition is a definite plus.
The  successful applicant will furthermore be motivated and able to conduct
research  independently,  as  well  as  collaborate  effectively with other
members  of  a  research  team. A certain affinity towards real-time vision
systems  and towards turning complex techniques into real-world practice is
essential. Language skills: good in English, basic in German.

Funding  for  the  Ph.D.  student  position is available immediately, for a
period  of 3-4 years. External academic supervision to be provided by Univ.
of Mannheim (Prof. Dr. C. Schnörr).

Prospective applicants please email cover letter (explaining suitability),
resume,  copy of academic record,  references, and any supporting materials
(e.g. MS Thesis, publications, GRE scores) to

Prof. Dr. Dariu Gavrila
Machine Perception, GRE/AP
DaimlerChrysler Research & Technology
Wilhelm Runge St. 11, 89081 Ulm, Germany
[my-first-name].[my-last-name]@DaimlerChrysler.com

For more background information, see
http://www.gavrila.net/Computer_Vision/Research/Pedestrian_Detection/pedestrian_detection.html