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Computer Vision: A Modern Approach

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TLDR
The accessible presentation of this book gives both a general view of the entire computer vision enterprise and also offers sufficient detail to be able to build useful applications as discussed by the authors, which includes essential topics that either reflect practical significance or are of theoretical importance.
Abstract
From the Publisher: The accessible presentation of this book gives both a general view of the entire computer vision enterprise and also offers sufficient detail to be able to build useful applications. Users learn techniques that have proven to be useful by first-hand experience and a wide range of mathematical methods. A CD-ROM with every copy of the text contains source code for programming practice, color images, and illustrative movies. Comprehensive and up-to-date, this book includes essential topics that either reflect practical significance or are of theoretical importance. Topics are discussed in substantial and increasing depth. Application surveys describe numerous important application areas such as image based rendering and digital libraries. Many important algorithms broken down and illustrated in pseudo code. Appropriate for use by engineers as a comprehensive reference to the computer vision enterprise.

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Journal ArticleDOI

Visual servo control. I. Basic approaches

TL;DR: This paper is the first of a two-part series on the topic of visual servo control using computer vision data in the servo loop to control the motion of a robot using basic techniques that are by now well established in the field.
Journal ArticleDOI

Interaction ruling animal collective behavior depends on topological rather than metric distance: Evidence from a field study

TL;DR: It is argued that a topological interaction is indispensable to maintain a flock's cohesion against the large density changes caused by external perturbations, typically predation, and supported by numerical simulations.
Book ChapterDOI

Object Recognition as Machine Translation: Learning a Lexicon for a Fixed Image Vocabulary

TL;DR: This work shows how to cluster words that individually are difficult to predict into clusters that can be predicted well, and cannot predict the distinction between train and locomotive using the current set of features, but can predict the underlying concept.
Journal ArticleDOI

Matching words and pictures

TL;DR: A new approach for modeling multi-modal data sets, focusing on the specific case of segmented images with associated text, is presented, and a number of models for the joint distribution of image regions and words are developed, including several which explicitly learn the correspondence between regions and Words.
Journal ArticleDOI

Image change detection algorithms: a systematic survey

TL;DR: In this paper, the authors present a systematic survey of the common processing steps and core decision rules in modern change detection algorithms, including significance and hypothesis testing, predictive models, the shading model, and background modeling.