Computer Vision

SERIES EDITORS:
Gerard Medioni, University of Southern California
Sven Dickinson, University of Toronto
This series covers topics pertaining to computer vision and pattern recognition. The scope will largely follow the purview of premier computer science conferences, such as ICCV, CVPR, and ECCV. Potential topics include, but not are limited to: Applications and Case Studies for Computer Vision; Color, Illumination, and Texture; Computational Photography and Video; Early and Biologically-inspired Vision; Face and Gesture Analysis; Illumination and Reflectance Modeling; Image-Based Modeling; Image and Video Retrieval; Medical Image Analysis; Motion and Tracking; Object Detection, Recognition, and Categorization; Segmentation and Grouping; Sensors; Shape-from-X; Stereo and Structure from Motion; Shape Representation and Matching; Statistical Methods and Learning; Performance Evaluation; Video Analysis and Event Recognition.

Editor Bios


Extreme Value Theory-Based Methods for Visual Recognition Extreme Value Theory-Based Methods for Visual Recognition
Walter J. Scheirer
A common feature of many approaches to modeling sensory statistics is an emphasis on capturing the "average." From early representations in the brain, to highly abstracted class categories in machine learning for classification tasks, central-tendenc...
Publication Date: February, 2017

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Data Association for Multi-Object Visual Tracking Data Association for Multi-Object Visual Tracking
Margrit Betke, Zheng Wu
In the human quest for scientific knowledge, empirical evidence is collected by visual perception. Tracking with computer vision takes on the important role to reveal complex patterns of motion that exist in the world we live in. Multi-object trackin...
Publication Date: October, 2016

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Ellipse Fitting for Computer Vision Ellipse Fitting for Computer Vision
Kenichi Kanatani , Yasuyuki Sugaya , Yasushi Kanazawa
Because circular objects are projected to ellipses in images, ellipse fitting is a first step for 3-D analysis of circular objects in computer vision applications. For this reason, the study of ellipse fitting began as soon as computers came into us...
Publication Date: April, 2016

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Computational Methods for Integrating Vision and Language Computational Methods for Integrating Vision and Language
Kobus Barnard
"This is clearly the most comprehensive and thoughtful compendium of knowledge on language/vision integration out there, and I'm sure it will be a valuable resource to many researchers and instructors." - Sven Dickinson, Series Edito...
Publication Date: April, 2016

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Background Subtraction Background Subtraction
Ahmed Elgammal
Background subtraction is a widely used concept for detection of moving objects in videos. In the last two decades there has been a lot of development in designing algorithms for background subtraction, as well as wide use of these algorithms in vari...
Publication Date: 12/01/2014

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Vision-Based Interaction Vision-Based Interaction
Matthew Turk, Gang Hua
In its early years, the field of computer vision was largely motivated by researchers seeking computational models of biological vision and solutions to practical problems in manufacturing, defense, and medicine. For the past two decades or so, ther...
Publication Date: 10/01/2013

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Camera Networks Camera Networks
Amit Roy-Chowdhury, Bi Song
As networks of video cameras are installed in many applications like security and surveillance, environmental monitoring, disaster response, and assisted living facilities, among others, image understanding in camera networks is becoming an important...
Publication Date: 01/01/2012

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Deformable Surface 3D Reconstruction from Monocular Images Deformable Surface 3D Reconstruction from Monocular Images
Matthieu Salzmann, Pascal Fua
Being able to recover the shape of 3D deformable surfaces from a single video stream would make it possible to field reconstruction systems that run on widely available hardware without requiring specialized devices. However, because many different 3...
Publication Date: 01/01/2010

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Boosting-Based Face Detection and Adaptation Boosting-Based Face Detection and Adaptation
Cha Zhang, Zhengyou Zhang
Face detection, because of its vast array of applications, is one of the most active research areas in computer vision. In this book, we review various approaches to face detection developed in the past decade, with more emphasis on boosting-based le...
Publication Date: 01/01/2010

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Image-Based Modeling of Plants and Trees Image-Based Modeling of Plants and Trees
Sing Bang Kang, Long Quan
Plants and trees are among the most complex natural objects. Much work has been done attempting to model them, with varying degrees of success. In this book, we review the various approaches in computer graphics, which we categorize as rule-based, im...
Publication Date: 01/01/2009

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