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Computer Vision/Computer Graphics Collaboration Techniques

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Cover of 'Computer Vision/Computer Graphics Collaboration Techniques'

Table of Contents

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    Book Overview
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    Chapter 1 Bundle Adjustment for Stereoscopic 3D
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    Chapter 2 3D Modeling of Haussmannian Facades
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    Chapter 3 Lung Cancer Detection from Thoracic CT Scans Using 3-D Deformable Models Based on Statistical Anatomical Analysis
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    Chapter 4 An Evaluation on Estimators for Stochastic and Heuristic Based Cost Functions Using the Epipolar-Constraint
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    Chapter 5 Facial Movement Based Recognition
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    Chapter 6 Towards Temporally-Coherent Video Matting
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    Chapter 7 Leaf Segmentation and Tracking Using Probabilistic Parametric Active Contours
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    Chapter 8 Gallbladder Segmentation from 2–D Ultrasound Images Using Active Contour Models and Gradient Vector Flow
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    Chapter 9 Multi-view Alpha Matte for Free Viewpoint Rendering
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    Chapter 10 Using Spatially Distributed Patterns for Multiple View Camera Calibration
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    Chapter 11 Optimal Gabor Filters and Haralick Features for the Industrial Polarization Imaging
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    Chapter 12 Joint Histogram Modelling for Segmentation Multiple Sclerosis Lesions
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    Chapter 13 Surface Reconstruction of Scenes Using a Catadioptric Camera
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    Chapter 14 Creating Chinkin Works in the Virtual Space
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    Chapter 15 Real-Time Multi-view Human Motion Tracking Using 3D Model and Latency Tolerant Parallel Particle Swarm Optimization
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    Chapter 16 Snap Image Composition
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    Chapter 17 Towards the Automatic Generation of 3D Photo-Realistic Avatars Using 3D Scanned Data
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    Chapter 18 Content Based Image Retrieval Using Visual-Words Distribution Entropy
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    Chapter 19 Video Summarization Using a Self-Growing and Self-Organized Neural Gas Network
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    Chapter 20 Real-Time Upper-Body Human Pose Estimation Using a Depth Camera
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    Chapter 21 Image Matting with Transductive Inference
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    Chapter 22 A New Buckling Model for Cloth Simulation
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    Chapter 23 A Public System for Image Based 3D Model Generation
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    Chapter 24 A Novel Approach to Image Assessment by Seeking Unification of Subjective and Objective Criteria Based on Supervised Learning
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Computer Vision/Computer Graphics Collaboration Techniques
Published by
Springer Berlin Heidelberg, October 2011
DOI 10.1007/978-3-642-24136-9
978-3-64-224135-2, 978-3-64-224136-9

Gagalowicz, André, Philips, Wilfried, Gagalowicz, André, Philips, Wilfried

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 29 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Colombia 1 3%
France 1 3%
Switzerland 1 3%
Unknown 26 90%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 8 28%
Student > Master 6 21%
Researcher 6 21%
Student > Doctoral Student 4 14%
Professor 1 3%
Other 3 10%
Unknown 1 3%
Readers by discipline Count As %
Computer Science 14 48%
Engineering 9 31%
Agricultural and Biological Sciences 1 3%
Energy 1 3%
Earth and Planetary Sciences 1 3%
Other 0 0%
Unknown 3 10%