Takeo Kanade   Takeo Kanade

Takeo Kanade is the U. A. and Helen Whitaker University Professor of Computer Science and Robotics and the director of Quality of Life Technology Engineering Research Center at Carnegie Mellon University. He received his Doctoral degree in Electrical Engineering from Kyoto University, Japan, in 1974. After holding a faculty position in the Department of Information Science, Kyoto University, he joined Carnegie Mellon University in 1980. He was the Director of the Robotics Institute from 1992 to 2001. He also founded the Digital Human Research Center in Tokyo and served as the founding director from 2001 to 2010.

Dr. Kanade works in multiple areas of robotics: computer vision, multi-media, manipulators, autonomous mobile robots, medical robotics and sensors. He has written more than 400 technical papers and reports in these areas, and holds more than 20 patents. He has been the principal investigator of more than a dozen major vision and robotics projects at Carnegie Mellon.
Gavrila Dariu   Dariu Gavrila
Daimler and University of Amsterdam

Dariu M. Gavrila received the PhD degree in computer science from the University of Maryland at College Park in 1996. Since 1997, he has been a Senior Research Scientist at Daimler R&D in Ulm, Germany. In 2003, he was further appointed professor at the University of Amsterdam, chairing the area of Intelligent Perception Systems (part time).

Over the past 15 years, Prof. Gavrila has focused on visual systems for
detecting humans and their activity, with application to intelligent vehicles and surveillance. He led the multi-year pedestrian detection research effort at Daimler, which was successfully incorporated in the Mercedes-Benz E-Class and S-Class models (2013). He is frequently cited in the scientific literature and he received the I/O 2007 Award from the Netherlands Organisation for Scientific Research (NWO) as well as several conference paper awards.

Gavrila Dariu   Martial Hebert
School of Computer Science, Carnegie Mellon University, USA

Martial Hebert's work is in the areas of computer vision and perception for autonomous systems. His interests are in the interpretation of perception data (both 2-D and 3-D), including building models of environments. Current research directions include:
  • Efficient techniques for object/category recognition
  • Use of contextual information, in particular 3-D geometry from images, for scene analysis
  • Symbolic knowledge for scene interpretation and reconstruction
  • Motion analysis for feature extraction and event detection in video clips
  • Efficient tools for the analysis of dynamic 3-D point clouds ("3-D signal processing")
  • Perception for autonomous systems
  • Detection, tracking, and prediction in dynamic environments