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Computer Vision -- ACCV 2014

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Cover of 'Computer Vision -- ACCV 2014'

Table of Contents

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    Book Overview
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    Chapter 1 Improving Human Action Recognition Using Score Distribution and Ranking
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    Chapter 2 Context-Aware Activity Forecasting
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    Chapter 3 DMM-Pyramid Based Deep Architectures for Action Recognition with Depth Cameras
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    Chapter 4 Discriminative Orderlet Mining for Real-Time Recognition of Human-Object Interaction
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    Chapter 5 Anomaly Detection via Local Coordinate Factorization and Spatio-Temporal Pyramid
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    Chapter 6 Intrinsic Image Decomposition from Pair-Wise Shading Ordering
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    Chapter 7 Never Get Lost Again: Vision Based Navigation Using StreetView Images
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    Chapter 8 Qualitative and quantitative spatio-temporal relations in daily living activity recognition
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    Chapter 9 Blur-Resilient Tracking Using Group Sparsity
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    Chapter 10 Visual Tracking via Supervised Similarity Matching
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    Chapter 11 Multi-state Discriminative Video Segment Selection for Complex Event Classification
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    Chapter 12 Action Recognition in the Presence of One Egocentric and Multiple Static Cameras
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    Chapter 13 Robust Online Visual Tracking with a Single Convolutional Neural Network
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    Chapter 14 Bi-Stage Large Point Set Registration Using Gaussian Mixture Models
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    Chapter 15 Enhanced Sequence Matching for Action Recognition from 3D Skeletal Data
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    Chapter 16 Multi-label Discriminative Weakly-Supervised Human Activity Recognition and Localization
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    Chapter 17 Action-Gons: Action Recognition with a Discriminative Dictionary of Structured Elements with Varying Granularity
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    Chapter 18 Fast Inference of Contaminated Data for Real Time Object Tracking
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    Chapter 19 Computer Vision -- ACCV 2014
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    Chapter 20 A Rotation-Invariant Regularization Term for Optical Flow Related Problems
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    Chapter 21 Landmark-Based Inductive Model for Robust Discriminative Tracking
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    Chapter 22 Extended Co-occurrence HOG with Dense Trajectories for Fine-Grained Activity Recognition
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    Chapter 23 Motion Based Foreground Detection and Poselet Motion Features for Action Recognition
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    Chapter 24 Global Motion Estimation from Relative Measurements in the Presence of Outliers
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    Chapter 25 Clustering Ensemble Tracking
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    Chapter 26 Query Based Adaptive Re-ranking for Person Re-identification
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    Chapter 27 Improved Color Patch Similarity Measure Based Weighted Median Filter
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    Chapter 28 Efficient Pose-Based Action Recognition
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    Chapter 29 Tracking Multiple People Online and in Real Time
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    Chapter 30 Optimizing Storage Intensive Vision Applications to Device Capacity
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    Chapter 31 MTS: A Multiple Temporal Scale Tracker Handling Occlusion and Abrupt Motion Variation
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    Chapter 32 Video Annotation by Incremental Learning from Grouped Heterogeneous Sources
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    Chapter 33 A Novel Group-Sparsity-Optimization-Based Feature Selection Model for Complex Interaction Recognition
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    Chapter 34 Boosting-Based Visual Tracking Using Structural Local Sparse Descriptors
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    Chapter 35 Coupling Multiple Alignments and Re-ranking for Low-Latency Online Multi-target Tracking
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    Chapter 36 Determining Interacting Objects in Human-Centric Activities via Qualitative Spatio-Temporal Reasoning
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    Chapter 37 Enhanced Laplacian Group Sparse Learning with Lifespan Outlier Rejection for Visual Tracking
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    Chapter 38 Cross-view Action Recognition via Dual-Codebook and Hierarchical Transfer Framework
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    Chapter 39 Stereo Ground Truth with Error Bars
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    Chapter 40 Separation of Reflection Components by Sparse Non-negative Matrix Factorization
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    Chapter 41 Spatiotemporal Derivative Pattern: A Dynamic Texture Descriptor for Video Matching
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    Chapter 42 Weakly Supervised Action Recognition and Localization Using Web Images
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    Chapter 43 A Game-Theoretic Probabilistic Approach for Detecting Conversational Groups
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Title
Computer Vision -- ACCV 2014
Published by
Springer International Publishing, April 2015
DOI 10.1007/978-3-319-16814-2
ISBNs
978-3-31-916813-5, 978-3-31-916814-2
Editors

Cremers, Daniel, Reid, Ian, Saito, Hideo, Yang, Ming-Hsuan

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X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 5 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 5 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 1 20%
Student > Postgraduate 1 20%
Student > Master 1 20%
Unknown 2 40%
Readers by discipline Count As %
Computer Science 2 40%
Engineering 1 20%
Unknown 2 40%