Video Google: A Text Retrieval Approach to Object Matching in Videos
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Recognizing Human Actions: A Local SVM Approach
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 3 - Volume 03
A Spectral Technique for Correspondence Problems Using Pairwise Constraints
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
Graphical Models and Point Pattern Matching
IEEE Transactions on Pattern Analysis and Machine Intelligence
Feature Correspondence Via Graph Matching: Models and Global Optimization
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part II
Spatial-Temporal correlatons for unsupervised action classification
WMVC '08 Proceedings of the 2008 IEEE Workshop on Motion and video Computing
Trajectory representation using Gabor features for motion-based video retrieval
Pattern Recognition Letters
A Path Following Algorithm for the Graph Matching Problem
IEEE Transactions on Pattern Analysis and Machine Intelligence
Comparing evaluation protocols on the KTH dataset
HBU'10 Proceedings of the First international conference on Human behavior understanding
Modeling temporal structure of decomposable motion segments for activity classification
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part II
Recognizing and Localizing Individual Activities through Graph Matching
AVSS '10 Proceedings of the 2010 7th IEEE International Conference on Advanced Video and Signal Based Surveillance
Robust sequence alignment for actor-object interaction recognition: Discovering actor-object states
Computer Vision and Image Understanding
Computer Vision and Image Understanding
Action recognition with appearance-motion features and fast search trees
Computer Vision and Image Understanding
Dynamic Programming and Graph Algorithms in Computer Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
Activity Modeling Using Event Probability Sequences
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
Efficient activity detection with max-subgraph search
CVPR '12 Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
A graph-matching kernel for object categorization
ICCV '11 Proceedings of the 2011 International Conference on Computer Vision
A "string of feature graphs" model for recognition of complex activities in natural videos
ICCV '11 Proceedings of the 2011 International Conference on Computer Vision
Semi-supervised learning and optimization for hypergraph matching
ICCV '11 Proceedings of the 2011 International Conference on Computer Vision
Human behavior understanding for robotics
HBU'12 Proceedings of the Third international conference on Human Behavior Understanding
Graph-based analysis of physical exercise actions
Proceedings of the 1st ACM international workshop on Multimedia indexing and information retrieval for healthcare
Graph-based approach for human action recognition using spatio-temporal features
Journal of Visual Communication and Image Representation
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Graph matching is one of the principal methods to formulate the correspondence between two set of points in computer vision and pattern recognition. However, most formulations are based on the minimization of a difficult energy function which is known to be NP-hard. Traditional methods solve the minimization problem approximately. In this paper, we show that an efficient solution can be obtained by exactly solving an approximated problem instead of approximately solving the original problem. We derive an exact minimization algorithm and successfully apply it to action recognition in videos. In this context, we take advantage of special properties of the time domain, in particular causality and the linear order of time, and propose a novel spatio-temporal graphical structure.