Learning OpenCV

Acknowledgments

A long-term open source effort sees many people come and go, each contributing in different ways. The list of contributors to this library is far too long to list here, but see the …/opencv/docs/HTML/Contributors/doc_contributors.html file that ships with OpenCV.

Thanks for Help on OpenCV

Intel is where the library was born and deserves great thanks for supporting this project the whole way through. Open source needs a champion and enough development support in the beginning to achieve critical mass. Intel gave it both. There are not many other companies where one could have started and maintained such a project through good times and bad. Along the way, OpenCV helped give rise to—and now takes (optional) advantage of—Intel's Integrated Performance Primitives, which are hand-tuned assembly language routines in vision, signal processing, speech, linear algebra, and more. Thus the lives of a great commercial product and an open source product are intertwined.

Mark Holler, a research manager at Intel, allowed OpenCV to get started by knowingly turning a blind eye to the inordinate amount of time being spent on an unofficial project back in the library's earliest days. As divine reward, he now grows wine up in Napa's Mt. Veeder area. Stuart Taylor in the Performance Libraries group at Intel enabled OpenCV by letting us "borrow" part of his Russian software team. Richard Wirt was key to its continued growth and survival. As the first author took on management responsibility at Intel, lab director Bob Liang let OpenCV thrive; when Justin Rattner became CTO, we were able to put OpenCV on a more firm foundation under Software Technology Lab—supported by software guru Shinn-Horng Lee and indirectly under his manager, Paul Wiley. Omid Moghadam helped advertise OpenCV in the early days. Mohammad Haghighat and Bill Butera were great as technical sounding boards. Nuriel Amir, Denver Dash, John Mark Agosta, and Marzia Polito were of key assistance in launching the machine learning library. Rainer Lienhart, Jean-Yves Bouguet, Radek Grzeszczuk, and Ara Nefian were able technical contributors to OpenCV and great colleagues along the way; the first is now a professor, the second is now making use of OpenCV in some well-known Google projects, and the others are staffing research labs and start-ups. There were many other technical contributors too numerous to name.

On the software side, some individuals stand out for special mention, especially on the Russian software team. Chief among these is the Russian lead programmer Vadim Pisarevsky, who developed large parts of the library and also managed and nurtured the library through the lean times when boom had turned to bust; he, if anyone, is the true hero of the library. His technical insights have also been of great help during the writing of this book. Giving him managerial support and protection in the lean years was Valery Kuriakin, a man of great talent and intellect. Victor Eruhimov was there in the beginning and stayed through most of it. We thank Boris Chudinovich for all of the contour components.

Finally, very special thanks go to Willow Garage [WG], not only for its steady financial backing to OpenCV's future development but also for supporting one author (and providing the other with snacks and beverages) during the final period of writing this book.

Thanks for Help on the Book

While preparing this book, we had several key people contributing advice, reviews, and suggestions. Thanks to John Markoff, Technology Reporter at the New York Times for encouragement, key contacts, and general writing advice born of years in the trenches. To our reviewers, a special thanks go to Evgeniy Bart, physics postdoc at CalTech, who made many helpful comments on every chapter; Kjerstin Williams at Applied Minds, who did detailed proofs and verification until the end; John Hsu at Willow Garage, who went through all the example code; and Vadim Pisarevsky, who read each chapter in detail, proofed the function calls and the code, and also provided several coding examples. There were many other partial reviewers. Jean-Yves Bouguet at Google was of great help in discussions on the calibration and stereo chapters. Professor Andrew Ng at Stanford University provided useful early critiques of the machine learning chapter. There were numerous other reviewers for various chapters—our thanks to all of them. Of course, any errors result from our own ignorance or misunderstanding, not from the advice we received.

Finally, many thanks go to our editor, Michael Loukides, for his early support, numerous edits, and continued enthusiasm over the long haul.

Gary Adds…

With three young kids at home, my wife Sonya put in more work to enable this book than I did. Deep thanks and love—even OpenCV gives her recognition, as you can see in the face detection section example image. Further back, my technical beginnings started with the physics department at the University of Oregon followed by undergraduate years at UC Berkeley. For graduate school, I'd like to thank my advisor Steve Grossberg and Gail Carpenter at the Center for Adaptive Systems, Boston University, where I first cut my academic teeth. Though they focus on mathematical modeling of the brain and I have ended up firmly on the engineering side of AI, I think the perspectives I developed there have made all the difference. Some of my former colleagues in graduate school are still close friends and gave advice, support, and even some editing of the book: thanks to Frank Guenther, Andrew Worth, Steve Lehar, Dan Cruthirds, Allen Gove, and Krishna Govindarajan.

I specially thank Stanford University, where I'm currently a consulting professor in the AI and Robotics lab. Having close contact with the best minds in the world definitely rubs off, and working with Sebastian Thrun and Mike Montemerlo to apply OpenCV on Stanley (the robot that won the $2M DARPA Grand Challenge) and with Andrew Ng on STAIR (one of the most advanced personal robots) was more technological fun than a person has a right to have. It's a department that is currently hitting on all cylinders and simply a great environment to be in. In addition to Sebastian Thrun and Andrew Ng there, I thank Daphne Koller for setting high scientific standards, and also for letting me hire away some key interns and students, as well as Kunle Olukotun and Christos Kozyrakis for many discussions and joint work. I also thank Oussama Khatib, whose work on control and manipulation has inspired my current interests in visually guided robotic manipulation. Horst Haussecker at Intel Research was a great colleague to have, and his own experience in writing a book helped inspire my effort.

Finally, thanks once again to Willow Garage for allowing me to pursue my lifelong robotic dreams in a great environment featuring world-class talent while also supporting my time on this book and supporting OpenCV itself.

Adrian Adds…

Coming from a background in theoretical physics, the arc that brought me through supercomputer design and numerical computing on to machine learning and computer vision has been a long one. Along the way, many individuals stand out as key contributors. I have had many wonderful teachers, some formal instructors and others informal guides. I should single out Professor David Dorfan of UC Santa Cruz and Hartmut Sadrozinski of SLAC for their encouragement in the beginning, and Norman Christ for teaching me the fine art of computing with the simple edict that "if you can not make the computer do it, you don't know what you are talking about". Special thanks go to James Guzzo, who let me spend time on this sort of thing at Intel—even though it was miles from what I was supposed to be doing—and who encouraged my participation in the Grand Challenge during those years. Finally, I want to thank Danny Hillis for creating the kind of place where all of this technology can make the leap to wizardry and for encouraging my work on the book while at Applied Minds.

I also would like to thank Stanford University for the extraordinary amount of support I have received from them over the years. From my work on the Grand Challenge team with Sebastian Thrun to the STAIR Robot with Andrew Ng, the Stanford AI Lab was always generous with office space, financial support, and most importantly ideas, enlightening conversation, and (when needed) simple instruction on so many aspects of vision, robotics, and machine learning. I have a deep gratitude to these people, who have contributed so significantly to my own growth and learning.

No acknowledgment or thanks would be meaningful without a special thanks to my lady Lyssa, who never once faltered in her encouragement of this project or in her willingness to accompany me on trips up and down the state to work with Gary on this book. My thanks and my love go to her.