Additional order info. An applied introduction to modern computer vision, focusing on a set of computational techniques for 3-D imaging. Covers a wide range of fundamental problems encountered within computer vision and provides detailed algorithmic and theoretical solutions for each. Each chapter concentrates on a specific problem and solves it by building on previous results.
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Indian Institute of Technology Gandhinagar. Lecture Hall - Shed 5 O ffice - Shed 5 Teaching Assistant - Rajendra Nagar. The world we live has three dimensions 3D. Human visual system has evolved to perceive all these dimensions.
However, the images we capture using conventional cameras are just the 2D projections of the 3D world. In 3D Computer Vision course, we shall explore various techniques for recovering the missing third dimension depth information from 2D images using primarily variational methods and projective geometry concepts.
The course contents would enable the student to reconstruct the 3D real world scene from 2D images by various methods. The applications of this course range from cultural heritage to medical imaging, from robot navigation to 3D modeling. This course is also prescribed for minor degree in Computer Science. The book by Marr provides a viewpoint based on visual neuroscience concepts. The last 5 books can be used as reference for certain topics.
Apart from these books, some topics would be taught from selected research papers. Lecture notes you make in the classroom will provide pointers to look into topics in different books listed above. The topics taught in a lecture may have evolved from multiple books and research papers. Reading books would certainly aid lectures but can never replace the lectures. These suggested readings supplement the textbooks and reference books to understand various mathematical concepts in depth.
Exposure to Signals and Systems course at the UG level is required. Use Piazza. Robot Vision. The MIT Press. Hartley R. Szeliski, R. Computer Vision: Algorithms and Applications. Springer-Verlag New York Inc. Available Online.
Nixon, M. Third Edition. Academic Press. Davies, E. Forsyth, D. Computer Vision: A Modern Approach. Second Edition. Prentice Hall of India. Klette, R. Springer Publishing Company, Incorporated.
References Marr, D. Sonka, M. Image Processing, Analysis, and Machine Vision. Cengage Learning. Trucco, E. Prince, S. Computer Vision: Models, Learning, and Inference. Cambridge University Press. Available Online Ikeuchi, K. Computer Vision: A Reference Guide. Fisher, R. Dictionary of computer vision and image processing. Suggested Readings Trefethen, L.
Watkins, D. Courant, R. Gelfand, I. Lathi, B. Szeliski Chapter 3, Otsu's Threshold. Szeliski Chapter 4, Lowe's Paper. Achintya Bhowmik, Intel.
Introductory techniques for 3-D computer vision
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Introductory Techniques for 3D Computer Vision
Introductory Techniques for 3-D Computer Vision