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Computer Vision – ECCV 2012

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Table of Contents

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    Book Overview
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    Chapter 1 Tracking Feature Points in Uncalibrated Images with Radial Distortion
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    Chapter 2 Divergence-Free Motion Estimation
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    Chapter 3 Visual Tracking via Adaptive Tracker Selection with Multiple Features
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    Chapter 4 Image Enhancement Using Calibrated Lens Simulations
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    Chapter 5 Color Constancy, Intrinsic Images, and Shape Estimation
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    Chapter 6 A Fast Illumination and Deformation Insensitive Image Comparison Algorithm Using Wavelet-Based Geodesics
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    Chapter 7 Large-Scale Gaussian Process Classification with Flexible Adaptive Histogram Kernels
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    Chapter 8 Background Subtraction with Dirichlet Processes
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    Chapter 9 Mobile Product Image Search by Automatic Query Object Extraction
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    Chapter 10 Analyzing the Subspace Structure of Related Images: Concurrent Segmentation of Image Sets.
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    Chapter 11 Artistic Image Classification: An Analysis on the PRINTART Database
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    Chapter 12 Detecting Actions, Poses, and Objects with Relational Phraselets
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    Chapter 13 Action Recognition with Exemplar Based 2.5D Graph Matching
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    Chapter 14 Cost-Sensitive Top-Down/Bottom-Up Inference for Multiscale Activity Recognition
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    Chapter 15 Activity Forecasting
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    Chapter 16 A Unified Framework for Multi-target Tracking and Collective Activity Recognition
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    Chapter 17 Camera Pose Estimation Using First-Order Curve Differential Geometry
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    Chapter 18 Beyond Feature Points: Structured Prediction for Monocular Non-rigid 3D Reconstruction
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    Chapter 19 Learning Spatially-Smooth Mappings in Non-Rigid Structure from Motion.
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    Chapter 20 In Defence of RANSAC for Outlier Rejection in Deformable Registration
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    Chapter 21 A Tensor Voting Approach for Multi-view 3D Scene Flow Estimation and Refinement
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    Chapter 22 Two-View Underwater Structure and Motion for Cameras under Flat Refractive Interfaces
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    Chapter 23 Reading Ancient Coins: Automatically Identifying Denarii Using Obverse Legend Seeded Retrieval
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    Chapter 24 Robust and Practical Face Recognition via Structured Sparsity
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    Chapter 25 Recognizing Materials from Virtual Examples
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    Chapter 26 Scene Recognition on the Semantic Manifold
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    Chapter 27 Unsupervised Temporal Commonality Discovery
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    Chapter 28 Finding People Using Scale, Rotation and Articulation Invariant Matching
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    Chapter 29 Measuring Image Distances via Embedding in a Semantic Manifold
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    Chapter 30 Efficient Point-to-Subspace Query in ℓ1 with Application to Robust Face Recognition
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    Chapter 31 Recognizing Complex Events Using Large Margin Joint Low-Level Event Model
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    Chapter 32 Multi-component Models for Object Detection
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    Chapter 33 Discriminative Decorrelation for Clustering and Classification
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    Chapter 34 Beyond Spatial Pyramids: A New Feature Extraction Framework with Dense Spatial Sampling for Image Classification
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    Chapter 35 Subspace Learning in Krein Spaces: Complete Kernel Fisher Discriminant Analysis with Indefinite Kernels
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    Chapter 36 A Novel Material-Aware Feature Descriptor for Volumetric Image Registration in Diffusion Tensor Space
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    Chapter 37 Efficient Closed-Form Solution to Generalized Boundary Detection
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    Chapter 38 Attribute Learning for Understanding Unstructured Social Activity
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    Chapter 39 Statistical Inference of Motion in the Invisible
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    Chapter 40 Going with the Flow: Pedestrian Efficiency in Crowded Scenes
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    Chapter 41 Reconstructing 3D Human Pose from 2D Image Landmarks
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    Chapter 42 Computer Vision – ECCV 2012
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    Chapter 43 TreeCANN - k-d Tree Coherence Approximate Nearest Neighbor Algorithm
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    Chapter 44 Robust Regression
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    Chapter 45 Domain Adaptive Dictionary Learning
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    Chapter 46 A robust and efficient doubly regularized metric learning approach
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    Chapter 47 A Discriminative Data-Dependent Mixture-Model Approach for Multiple Instance Learning in Image Classification
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    Chapter 48 No Bias Left behind: Covariate Shift Adaptation for Discriminative 3D Pose Estimation
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    Chapter 49 Labeling Images by Integrating Sparse Multiple Distance Learning and Semantic Context Modeling
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    Chapter 50 Exploiting the Circulant Structure of Tracking-by-Detection with Kernels
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    Chapter 51 Online Spatio-temporal Structural Context Learning for Visual Tracking
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    Chapter 52 Automatic Tracking of a Large Number of Moving Targets in 3D
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    Chapter 53 Towards Optimal Non-rigid Surface Tracking
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    Chapter 54 Full Body Performance Capture under Uncontrolled and Varying Illumination: A Shading-Based Approach
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    Chapter 55 Automatic Exposure Correction of Consumer Photographs
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    Chapter 56 Image Guided Tone Mapping with Locally Nonlinear Model
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    Chapter 57 A Comparison of the Statistical Properties of IQA Databases Relative to a Set of Newly Captured High-Definition Images
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    Chapter 58 Supervised Assessment of Segmentation Hierarchies
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    Chapter 59 Image Labeling on a Network: Using Social-Network Metadata for Image Classification
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    Chapter 60 Segmentation Based Particle Filtering for Real-Time 2D Object Tracking
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    Chapter 61 Online video segmentation by bayesian split-merge clustering
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    Chapter 62 Joint Classification-Regression Forests for Spatially Structured Multi-object Segmentation
Attention for Chapter 27: Unsupervised Temporal Commonality Discovery
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Chapter title
Unsupervised Temporal Commonality Discovery
Chapter number 27
Book title
Computer Vision – ECCV 2012
Published in
Lecture notes in computer science, January 2012
DOI 10.1007/978-3-642-33765-9_27
Book ISBNs
978-3-64-233764-2, 978-3-64-233765-9
Authors

Wen-Sheng Chu, Feng Zhou, Fernando De la Torre

Editors

Andrew Fitzgibbon, Svetlana Lazebnik, Pietro Perona, Yoichi Sato, Cordelia Schmid

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 45 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
France 2 4%
United Kingdom 1 2%
Unknown 42 93%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 16 36%
Researcher 10 22%
Student > Bachelor 5 11%
Student > Master 5 11%
Professor 3 7%
Other 4 9%
Unknown 2 4%
Readers by discipline Count As %
Computer Science 34 76%
Engineering 4 9%
Agricultural and Biological Sciences 2 4%
Psychology 1 2%
Unknown 4 9%