9780521540513 - Multiple View Geometry in Computer Vision Second Edition by Hartley, Richard (36 results)

Condition: good. All pages and cover are intact. Dust jacket included if applicable, though it may be missing on hardcover editions. Spine and cover may show minor signs of wear including scuff marks, curls or bends to corners as well as cosmetic blemishes including stickers. Pages may contain limited notes or highlighting. "From the library of" labels may be present. Shrink wrap, dust covers, or boxed set packaging may be missing. Bundled media e.g., CDs, DVDs, access codes may not be included.

Condition: good. Signs of wear and consistent use.

Condition: acceptable. Fairly worn, but readable and intact. If applicable: Dust jacket, disc or access code may not be included.

paperback. Condition: Good. Normal wear from daily use. May include markings or highlighting.

paperback. Condition: Good. 2nd Edition. Ships in a BOX from Central Missouri! May not include working access code. Will not include dust jacket. Has used sticker(s) and some writing or highlighting. UPS shipping for most packages, (Priority Mail for AK/HI/APO/PO Boxes).

Paperback. Condition: Very Good. The book has been read, but is in excellent condition. Pages are intact and not marred by notes or highlighting. The spine remains undamaged.

Condition: Good. Former library copy. Pages intact with minimal writing/highlighting. The binding may be loose and creased. Dust jackets/supplements are not included. Includes library markings. Stock photo provided. Product includes identifying sticker. Better World Books: Buy Books. Do Good.

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Condition: good. May show signs of wear, highlighting, writing, and previous use. This item may be a former library book with typical markings. No guarantee on products that contain supplements Your satisfaction is 100% guaranteed. Twenty-five year bookseller with shipments to over fifty million happy customers.

Condition: New.

Paperback. Condition: New. A basic problem in computer vision is to understand the structure of a real world scene given several images of it. Techniques for solving this problem are taken from projective geometry and photogrammetry. Here, the authors cover the geometric principles and their algebraic representation in terms of camera projection matrices, the fundamental matrix and the trifocal tensor. The theory and methods of computation of these entities are discussed with real examples, as is their use in the reconstruction of scenes from multiple images. The new edition features an extended introduction covering the key ideas in the book (which itself has been updated with additional examples and appendices) and significant new results which have appeared since the first edition. Comprehensive background material is provided, so readers familiar with linear algebra and basic numerical methods can understand the projective geometry and estimation algorithms presented, and implement the algorithms directly from the book.

Paperback. Condition: new. New Copy. Customer Service Guaranteed.

Condition: good. May show signs of wear, highlighting, writing, and previous use. This item may be a former library book with typical markings. No guarantee on products that contain supplements Your satisfaction is 100% guaranteed. Twenty-five year bookseller with shipments to over fifty million happy customers.

Condition: New.

Condition: New. In.

paperback. Condition: New. In shrink wrap. Looks like an interesting title!

Paperback. Condition: New.

Condition: As New. Unread book in perfect condition.

Condition: New.

Paperback. Condition: new. Paperback. A basic problem in computer vision is to understand the structure of a real world scene given several images of it. Techniques for solving this problem are taken from projective geometry and photogrammetry. Here, the authors cover the geometric principles and their algebraic representation in terms of camera projection matrices, the fundamental matrix and the trifocal tensor. The theory and methods of computation of these entities are discussed with real examples, as is their use in the reconstruction of scenes from multiple images. The new edition features an extended introduction covering the key ideas in the book (which itself has been updated with additional examples and appendices) and significant new results which have appeared since the first edition. Comprehensive background material is provided, so readers familiar with linear algebra and basic numerical methods can understand the projective geometry and estimation algorithms presented, and implement the algorithms directly from the book. The theory and practice of scene reconstruction are described in detail in a unified framework. The new edition features an extended introduction covering the key ideas in the book (which itself has been updated with additional examples and appendices) and significant new results which have appeared since the first edition. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Condition: New. pp. xvi + 655 2nd Edition.

Condition: As New. Unread book in perfect condition.

Condition: New. pp. xvi + 655.

Paperback. Condition: Like New. Like New. book.

Paperback. Condition: New. A basic problem in computer vision is to understand the structure of a real world scene given several images of it. Techniques for solving this problem are taken from projective geometry and photogrammetry. Here, the authors cover the geometric principles and their algebraic representation in terms of camera projection matrices, the fundamental matrix and the trifocal tensor. The theory and methods of computation of these entities are discussed with real examples, as is their use in the reconstruction of scenes from multiple images. The new edition features an extended introduction covering the key ideas in the book (which itself has been updated with additional examples and appendices) and significant new results which have appeared since the first edition. Comprehensive background material is provided, so readers familiar with linear algebra and basic numerical methods can understand the projective geometry and estimation algorithms presented, and implement the algorithms directly from the book.

Paperback. Condition: Sehr gut. Gebraucht - Sehr gut SG - leichte Beschädigungen oder Verschmutzungen, ungelesenes Mängelexemplar, gestempelt - A basic problem in computer vision is to understand the structure of a real world scene given several images of it. Techniques for solving this problem are taken from projective geometry and photogrammetry. Here, the authors cover the geometric principles and their algebraic representation in terms of camera projection matrices, the fundamental matrix and the trifocal tensor. The theory and methods of computation of these entities are discussed with real examples, as is their use in the reconstruction of scenes from multiple images. The new edition features an extended introduction covering the key ideas in the book (which itself has been updated with additional examples and appendices) and significant new results which have appeared since the first edition. Comprehensive background material is provided, so readers familiar with linear algebra and basic numerical methods can understand the projective geometry and estimation algorithms presented, and implement the algorithms directly from the book.

Paperback. Condition: Brand New. 2nd edition. 672 pages. 9.50x7.00x0.25 inches. In Stock.

Condition: New. 2004. 2nd Edition. Paperback. How to reconstruct scenes from images using geometry and algebra, with applications to computer vision. Num Pages: 670 pages, 36 colour illus. 35 tables 124 exercises. BIC Classification: TJFM1; UYQV. Category: (P) Professional & Vocational. Dimension: 246 x 175 x 30. Weight in Grams: 1296. 672 pages, 36 colour illus. 35 tables 124 exercises. How to reconstruct scenes from images using geometry and algebra, with applications to computer vision. Cateogry: (P) Professional & Vocational. BIC Classification: TJFM1; UYQV. Dimension: 246 x 175 x 30. Weight: 1308. . . . . . Books ship from the US and Ireland.

Paperback. Condition: new. Paperback. A basic problem in computer vision is to understand the structure of a real world scene given several images of it. Techniques for solving this problem are taken from projective geometry and photogrammetry. Here, the authors cover the geometric principles and their algebraic representation in terms of camera projection matrices, the fundamental matrix and the trifocal tensor. The theory and methods of computation of these entities are discussed with real examples, as is their use in the reconstruction of scenes from multiple images. The new edition features an extended introduction covering the key ideas in the book (which itself has been updated with additional examples and appendices) and significant new results which have appeared since the first edition. Comprehensive background material is provided, so readers familiar with linear algebra and basic numerical methods can understand the projective geometry and estimation algorithms presented, and implement the algorithms directly from the book. The theory and practice of scene reconstruction are described in detail in a unified framework. The new edition features an extended introduction covering the key ideas in the book (which itself has been updated with additional examples and appendices) and significant new results which have appeared since the first edition. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - A basic problem in computer vision is to understand the structure of a real world scene given several images of it. Techniques for solving this problem are taken from projective geometry and photogrammetry. Here, the authors cover the geometric principles and their algebraic representation in terms of camera projection matrices, the fundamental matrix and the trifocal tensor. The theory and methods of computation of these entities are discussed with real examples, as is their use in the reconstruction of scenes from multiple images. The new edition features an extended introduction covering the key ideas in the book (which itself has been updated with additional examples and appendices) and significant new results which have appeared since the first edition. Comprehensive background material is provided, so readers familiar with linear algebra and basic numerical methods can understand the projective geometry and estimation algorithms presented, and implement the algorithms directly from the book.