Structured Computer Vision PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Structured Computer Vision PDF full book. Access full book title Structured Computer Vision by S Tanimoto. Download full books in PDF and EPUB format.
Author: S Tanimoto
Publisher: Elsevier
ISBN: 0323159265
Category : Technology & Engineering
Languages : en
Pages : 247
Get Book
Book Description
Structured Computer Vision
Author: S Tanimoto
Publisher: Elsevier
ISBN: 0323159265
Category : Technology & Engineering
Languages : en
Pages : 247
Get Book
Book Description
Structured Computer Vision
Author: Sebastian Nowozin
Publisher: Now Publishers Inc
ISBN: 1601984561
Category : Computers
Languages : en
Pages : 195
Get Book
Book Description
Structured Learning and Prediction in Computer Vision introduces the reader to the most popular classes of structured models in computer vision.
Author:
Publisher:
ISBN:
Category : Computer organization
Languages : en
Pages : 573
Get Book
Book Description
Author: Richard J. Radke
Publisher: Cambridge University Press
ISBN: 0521766877
Category : Business & Economics
Languages : en
Pages : 409
Get Book
Book Description
This book explores the fundamental computer vision principles and state-of-the-art algorithms used to create cutting-edge visual effects for movies and television. It describes classical computer vision algorithms and recent developments, features more than 200 original images, and contains in-depth interviews with Hollywood visual effects artists that tie the mathematical concepts to real-world filmmaking.
Author: Dongming Feng
Publisher: John Wiley & Sons
ISBN: 1119566584
Category : Science
Languages : en
Pages : 260
Get Book
Book Description
Provides comprehensive coverage of theory and hands-on implementation of computer vision-based sensors for structural health monitoring This book is the first to fill the gap between scientific research of computer vision and its practical applications for structural health monitoring (SHM). It provides a complete, state-of-the-art review of the collective experience that the SHM community has gained in recent years. It also extensively explores the potentials of the vision sensor as a fast and cost-effective tool for solving SHM problems based on both time and frequency domain analytics, broadening the application of emerging computer vision sensor technology in not only scientific research but also engineering practice. Computer Vision for Structural Dynamics and Health Monitoring presents fundamental knowledge, important issues, and practical techniques critical to successful development of vision-based sensors in detail, including robustness of template matching techniques for tracking targets; coordinate conversion methods for determining calibration factors to convert image pixel displacements to physical displacements; sensing by tracking artificial targets vs. natural targets; measurements in real time vs. by post-processing; and field measurement error sources and mitigation methods. The book also features a wide range of tests conducted in both controlled laboratory and complex field environments in order to evaluate the sensor accuracy and demonstrate the unique features and merits of computer vision-based structural displacement measurement. Offers comprehensive understanding of the principles and applications of computer vision for structural dynamics and health monitoring Helps broaden the application of the emerging computer vision sensor technology from scientific research to engineering practice such as field condition assessment of civil engineering structures and infrastructure systems Includes a wide range of laboratory and field testing examples, as well as practical techniques for field application Provides MATLAB code for most of the issues discussed including that of image processing, structural dynamics, and SHM applications Computer Vision for Structural Dynamics and Health Monitoring is ideal for graduate students, researchers, and practicing engineers who are interested in learning about this emerging sensor technology and advancing their applications in SHM and other engineering problems. It will also benefit those in civil and aerospace engineering, energy, and computer science.
Author: Simon J. D. Prince
Publisher: Cambridge University Press
ISBN: 1107011795
Category : Computers
Languages : en
Pages : 599
Get Book
Book Description
A modern treatment focusing on learning and inference, with minimal prerequisites, real-world examples and implementable algorithms.
Author: Ole Fogh Olsen
Publisher: Springer
ISBN: 3540320970
Category : Computers
Languages : en
Pages : 259
Get Book
Book Description
This book constitutes the thoroughly refereed post-proceedings of the First International Workshop on Deep Structure, Singularities, and Computer Vision, DSSCV 2005, held in Maastricht, The Netherlands in June 2005. The 14 revised full papers and 8 revised poster papers presented were carefully reviewed and selected for inclusion in the book. They represent the current state-of-the-art in understanding the relation between structural, topological information represented by singularities and metric information of signals, shapes, images, and colors.
Author: Richard Szeliski
Publisher: Springer Nature
ISBN: 3030343723
Category : Computers
Languages : en
Pages : 925
Get Book
Book Description
Computer Vision: Algorithms and Applications explores the variety of techniques used to analyze and interpret images. It also describes challenging real-world applications where vision is being successfully used, both in specialized applications such as image search and autonomous navigation, as well as for fun, consumer-level tasks that students can apply to their own personal photos and videos. More than just a source of “recipes,” this exceptionally authoritative and comprehensive textbook/reference takes a scientific approach to the formulation of computer vision problems. These problems are then analyzed using the latest classical and deep learning models and solved using rigorous engineering principles. Topics and features: Structured to support active curricula and project-oriented courses, with tips in the Introduction for using the book in a variety of customized courses Incorporates totally new material on deep learning and applications such as mobile computational photography, autonomous navigation, and augmented reality Presents exercises at the end of each chapter with a heavy emphasis on testing algorithms and containing numerous suggestions for small mid-term projects Includes 1,500 new citations and 200 new figures that cover the tremendous developments from the last decade Provides additional material and more detailed mathematical topics in the Appendices, which cover linear algebra, numerical techniques, estimation theory, datasets, and software Suitable for an upper-level undergraduate or graduate-level course in computer science or engineering, this textbook focuses on basic techniques that work under real-world conditions and encourages students to push their creative boundaries. Its design and exposition also make it eminently suitable as a unique reference to the fundamental techniques and current research literature in computer vision.
Author: Reinhard Klette
Publisher: Springer Science & Business Media
ISBN: 1447163206
Category : Computers
Languages : en
Pages : 441
Get Book
Book Description
This textbook provides an accessible general introduction to the essential topics in computer vision. Classroom-tested programming exercises and review questions are also supplied at the end of each chapter. Features: provides an introduction to the basic notation and mathematical concepts for describing an image and the key concepts for mapping an image into an image; explains the topologic and geometric basics for analysing image regions and distributions of image values and discusses identifying patterns in an image; introduces optic flow for representing dense motion and various topics in sparse motion analysis; describes special approaches for image binarization and segmentation of still images or video frames; examines the basic components of a computer vision system; reviews different techniques for vision-based 3D shape reconstruction; includes a discussion of stereo matchers and the phase-congruency model for image features; presents an introduction into classification and learning.
Author: David Forsyth
Publisher: Springer Science & Business Media
ISBN: 3540886818
Category : Computers
Languages : en
Pages : 833
Get Book
Book Description
The four-volume set comprising LNCS volumes 5302/5303/5304/5305 constitutes the refereed proceedings of the 10th European Conference on Computer Vision, ECCV 2008, held in Marseille, France, in October 2008. The 243 revised papers presented were carefully reviewed and selected from a total of 871 papers submitted. The four books cover the entire range of current issues in computer vision. The papers are organized in topical sections on recognition, stereo, people and face recognition, object tracking, matching, learning and features, MRFs, segmentation, computational photography and active reconstruction.
