This title is out of print.
David A. Forsyth, University of Illinois at Urbana-Champaign
Jean Ponce, Ecole Normale Superieure, Paris
Appropriate for upper-division undergraduate- and graduate-level courses in computer vision found in departments of Computer Science, Computer Engineering and Electrical Engineering.
This long anticipated book is the most complete treatment of modern computer vision methods by two of the leading authorities in the field. This accessible presentation gives both a general view of the entire computer vision enterprise and also offers sufficient detail for students to be able to build useful applications. Students will learn techniques that have proven to be useful by first-hand experience and a wide range of mathematical methods.
Allows instructors to select the most relevant topics for their students and encourages students to enrich their coursework by reading information on other computer vision topics.
Provides students with the most coherent synthesis of current views and teaches them successful techniques for building applications.
While the first half of each chapter is accessible to undergraduates, a good grasp of each chapter provides students with a professional level of skill and knowledge.
Teaches students about practical use of techniques and helps them gain insight into the demands of applications.
Enables students to build working systems easily as they can understand the construction of the final application.
Provides students with ample opportunity to apply the concepts in the text.
I. IMAGE FORMATION AND IMAGE MODELS.
II. EARLY VISION: JUST ONE IMAGE.
III. EARLY VISION: MULTIPLE IMAGES.
IV. MID-LEVEL VISION.
V. HIGH-LEVEL VISION: GEOMETRIC MODELS.
VI. HIGH-LEVEL VISION: PROBABILISTIC AND INFERENTIAL METHODS.
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David A. Forsyth received the D.Phil. degree in computer science from Oxford University. He is currently a Professor in the Computer Science Division at the University of California at Berkeley. He has co-authored over eighty technical papers on computer vision, computer graphics and machine learning and has co-edited two books.
Jean Ponce received the Ph.D. degree in Computer Science from the University of Paris Orsay. He is currently a Professor in the Department of Computer Science and the Beckman Institute at the University of Illinois at Urbana Champaign. Professor Ponce has written over a hundred conference and journal papers and co-edited two books on a range of subjects including computer vision and robotics.
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