书名：学习OpenCV（影印版）

作者：Gary Bradski, Adrian Kaehler 著

国内出版社：东南大学出版社

出版时间：2009年04月

页数：555

书号：978-7-5641-1629-3

原版书出版商：O'Reilly Media

 

Dr. Gary Rost Bradski is a consulting professor in the CS department at the Stanford
University AI Lab, where he mentors robotics, machine learning, and computer vision
research. He is also senior scientist at Willow Garage (http://www.willowgarage.com), a
recently founded robotics research institute/incubator. He holds a B.S. in EECS from
UC Berkeley and a Ph.D. from Boston University. He has 20 years of industrial experience
applying machine learning and computer vision, spanning option-trading operations
at First Union National Bank, to computer vision at Intel Research, to machine
learning in Intel Manufacturing, and several startup companies in between.
Gary started the Open Source Computer Vision Library (OpenCV, http://sourceforge.net/
projects/opencvlibrary), which is used around the world in research, in government, and
commercially; the statistical Machine Learning Library (which comes with OpenCV);
and the Probabilistic Network Library (PNL). Th e vision libraries helped develop a notable
part of the commercial Intel Performance Primitives Library (IPP, http://tinyurl
.com/36ua5s). Gary also organized the vision team for Stanley, the Stanford robot that won
the DARPA Grand Challenge autonomous race across the desert for a $2M team prize,
and he helped found the Stanford AI Robotics project at Stanford (http://www.cs.stanford
.edu/group/stair) working with Professor Andrew Ng. Gary has more than 50 publications
and 13 issued patents with 18 pending. He lives in Palo Alto, CA, with his wife and
three daughters and bikes road or mountain as much as he can.

 

 

 

Dr. Adrian Kaehler is a senior scientist at Applied Minds Corporation. His current research
includes topics in machine learning, statistical modeling, computer vision, and
robotics. Adrian received his Ph.D. in Th eoretical Physics from Columbia University in
1998. He 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.

 

 

Th e image on the cover of Learning OpenCV is a giant, or great, peacock moth (Saturnia
pyri). Native to Europe, the moth’s range includes southern France and Italy, the Iberian
Peninsula, and parts of Siberia and northern Africa. It inhabits open landscapes
with scattered trees and shrubs and can oft en be found in parklands, orchards, and
vineyards, where it rests under shade trees during the day.
Th e largest of the European moths, giant peacock moths have a wingspan of up to six
inches; their size and nocturnal nature can lead some observers to mistake them for
bats. Th eir wings are gray and grayish-brown with accents of white and yellow. In the
center of each wing, giant peacock moths have a large eyespot, a distinctive pattern most
commonly associated with the birds they are named for.