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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.
Computer Vision:
A Modern Approach
This extraordinary book gives a uniquely modern view of computer vision. Offering a general survey of the whole computer vision enterprise along with sufficient detail for readers to be able to build useful applications, this book is invaluable in providing a strategic overview of computer vision. With extensive use of probabalistic methods topics have been selected for their importance, both practically and theoreticallythe book gives the most coherent possible synthesis of current views, emphasizing techniques that have been successful in building applications. Readers engaged in computer graphics, robotics, image processing, and imaging in general will find this text an informative reference.
KEY FEATURES
I. IMAGE FORMATION AND IMAGE MODELS.
1. Cameras.II. EARLY VISION: JUST ONE IMAGE.
7. Linear Filters.III. EARLY VISION: MULTIPLE IMAGES.
10. The Geometry of Multiple Views.IV. MID-LEVEL VISION.
14. Segmentation By Clustering.V. HIGH-LEVEL VISION: GEOMETRIC MODELS.
18. Model-Based Vision.VI. HIGH-LEVEL VISION: PROBABILISTIC AND INFERENTIAL METHODS.
22. Finding Templates Using Classifiers.VII. APPLICATIONS.
25. Application: Finding in Digital Libraries.