Automatic recognition of film genres
Proceedings of the third ACM international conference on Multimedia
ACM Computing Surveys (CSUR)
The Earth Mover's Distance as a Metric for Image Retrieval
International Journal of Computer Vision
Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
Automatic Genre Identification for Content-Based Video Categorization
ICPR '00 Proceedings of the International Conference on Pattern Recognition - Volume 4
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
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Beyond Bags of Features: Spatial Pyramid Matching for Recognizing Natural Scene Categories
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Sports video categorizing method using camera motion parameters
ICME '03 Proceedings of the 2003 International Conference on Multimedia and Expo - Volume 1
Video classification using spatial-temporal features and PCA
ICME '03 Proceedings of the 2003 International Conference on Multimedia and Expo - Volume 3 (ICME '03) - Volume 03
Automatic Sports Video Genre Classification using Pseudo-2D-HMM
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 04
International Journal of Computer Vision
Evaluating bag-of-visual-words representations in scene classification
Proceedings of the international workshop on Workshop on multimedia information retrieval
Hidden Conditional Random Fields
IEEE Transactions on Pattern Analysis and Machine Intelligence
ICSC '08 Proceedings of the 2008 IEEE International Conference on Semantic Computing
Parallel neural networks for multimodal video genre classification
Multimedia Tools and Applications
Automatic sports genre categorization and view-type classification over large-scale dataset
MM '09 Proceedings of the 17th ACM international conference on Multimedia
The 1st workshop on large-scale multimedia retrieval and mining (LS-MMRM'09)
MM '09 Proceedings of the 17th ACM international conference on Multimedia
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Hierarchical decision making scheme for sports video categorisation with temporal post-processing
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
SURF: speeded up robust features
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part I
Using Webcast Text for Semantic Event Detection in Broadcast Sports Video
IEEE Transactions on Multimedia
Representations of Keypoint-Based Semantic Concept Detection: A Comprehensive Study
IEEE Transactions on Multimedia
Automatic Video Classification: A Survey of the Literature
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Automatic soccer video analysis and summarization
IEEE Transactions on Image Processing
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This paper presents an efficient and robust automatic process for large-scale sports video analysis. The proposed system firstly identifies the genre of the query video, and then accomplishes the interesting event detection task. The significance of this framework is its automatic characteristic in testing with minimum human involvement in training, as well as the scalability and expansibility in dealing with a large-scale dataset. Domain-knowledge independent local features are extracted from an input video sequence and a histogram based distribution representation is created using the bag-of-visual-words (BoW) model. In genre categorization, k-nearest neighbor (k-NN) classifiers with various dissimilarity measures are assessed and evaluated analytically. For the event detection, a hidden conditional random field (HCRF) structured prediction model is utilized. Overall, this framework demonstrates the efficiency and accuracy in processing voluminous data from sports collection and achieves various tasks in video analysis. It also demonstrates a potential technology transformation from the "laboratory bench" to commercial applications.