Learning OpenCV

Gary Rost Bradski is VP of Technology at Rexee Inc. a new startup applying machine learning to rich media on the web. He is also a consulting professor in the CS department at Stanford University, AI Lab where he mentors robotics, machine learning and computer vision research. He has a BS degree in EECS from U.C. Berkeley and a PhD from Boston University. His current interest is in applying highly scalable statistical models in computer vision and in continuous machine "learning in clutter" in robotics in general. Some external tools he started for thisare the Open Source Computer Vision Library, the statistical machine Learning Library (MLL comes with OpenCV), and the Probabilistic Network Library (PNL). OpenCV is used around the world in research, government and commercially (for example in wide use within Google). All libraries are open, and free on Source Forge for commercial or research purposes. The vision libraries use and helped develop a notable part of the commercial Intel performance primitives library (IPP). Gary led the vision team for Stanley, the Stanfordrobot that won the DARPA Grand Challenge autonomous race across the desert for a $2M team prize. He lives in Palo Alto with his wife and 3 daughters and bikes road or mountains as much as he can.Adrian Kaehler is a senior scientist at Applied Minds Corporation. His current research includes topics in machine learning, statistical modeling, and computer vision. Adrian received his Ph.D. in Theoretical Physics from Columbia university in 1998. Adrian has since held positions at Intel Corporation and the Stanford University AI Lab, and was a member of the winning Stanley race team in the DARPA Grand Challenge. He has a variety of published papers and patents in physics, electrical engineering, computer science, and robotics.