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Computer vision : a modern approach David A. Forsyth, Jean Ponce.

By: Contributor(s): Publication details: Noida: Pearson India Education, 2023.Edition: 2nd ed. contributions by Soumen Mukherjee, Arub Kumar BhattacharjeeDescription: 791 pages : illustrationsISBN:
  • 9789332550117 (pbk)
Subject(s): Genre/Form: DDC classification:
  • 006.37 F775C2 23
LOC classification:
  • TA1634 .F65 2012eb
Contents:
1. Geometric Camera Models -- 2. Light and Shading -- 3. Color -- 4. Linear Filters -- 5. Local Image Features -- 6. Texture -- 7. Stereopsis -- 8. Structure from Motion -- 9. Segmentation by Clustering -- 10. Grouping and Model Fitting -- 11. Tracking -- 12. Registration -- 13. Smooth Surfaces and Their Outlines -- 14. Range Data -- 15. Learning to Classify -- 16. Classifying Images -- 17. Detecting Objects in Images -- 18. Topics in Object Recognition -- 19. Image -Based Modeling and Rendering -- 20. Looking at People -- 21. Image Search and Retrieval -- 22. Optimization Techniques.
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Holdings
Item type Current library Collection Call number Status Notes Date due Barcode
Books Books Central Library, IISER Bhopal General Section 006.37 F775C2 (Browse shelf(Opens below)) Available 11213
Books Books Central Library, IISER Bhopal Reference Section Reference 006.37 F775C2 (Browse shelf(Opens below)) Not For Loan Reserve 11211
Books Books Central Library, IISER Bhopal General Section 006.37 F775C2 (Browse shelf(Opens below)) Available 11212
Browsing Central Library, IISER Bhopal shelves, Shelving location: Reference Section, Collection: Reference Close shelf browser (Hides shelf browser)
006.312 V23P Python data science handbook : 006.312 V23P Python data science handbook : 006.330151 Ac37R Reactive systems : 006.37 F775C2 Computer vision : 006.37 H255M2 Multiple view geometry in computer vision 006.38 Sch28M Mathematics of quantum computing: 006.3843 F955Q Quantum computation with topological codes :

Previous edition: Upper Saddle River, N.J.: Prentice Hall, 2003.

Includes bibliographical references and index.

1. Geometric Camera Models -- 2. Light and Shading -- 3. Color -- 4. Linear Filters -- 5. Local Image Features -- 6. Texture -- 7. Stereopsis -- 8. Structure from Motion -- 9. Segmentation by Clustering -- 10. Grouping and Model Fitting -- 11. Tracking -- 12. Registration -- 13. Smooth Surfaces and Their Outlines -- 14. Range Data -- 15. Learning to Classify -- 16. Classifying Images -- 17. Detecting Objects in Images -- 18. Topics in Object Recognition -- 19. Image -Based Modeling and Rendering -- 20. Looking at People -- 21. Image Search and Retrieval -- 22. Optimization Techniques.

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