A unified framework for semantic shot classification in sports videos
Proceedings of the tenth ACM international conference on Multimedia
Selection of Training Data for Neural Networks by a Genetic Algorithm
PPSN V Proceedings of the 5th International Conference on Parallel Problem Solving from Nature
A Motion Activity Descriptor and Its Extraction in Compressed Domain
PCM '01 Proceedings of the Second IEEE Pacific Rim Conference on Multimedia: Advances in Multimedia Information Processing
Automatic replay generation for soccer video broadcasting
Proceedings of the 12th annual ACM international conference on Multimedia
The Genetic Kernel Support Vector Machine: Description and Evaluation
Artificial Intelligence Review
Semi-supervised learning for semantic video retrieval
Proceedings of the 6th ACM international conference on Image and video retrieval
Classification of video events using 4-dimensional time-compressed motion features
Proceedings of the 6th ACM international conference on Image and video retrieval
SVM-Based Face Recognition Using Genetic Search for Frequency-Feature Subset Selection
ICISP '08 Proceedings of the 3rd international conference on Image and Signal Processing
Video event detection using motion relativity and visual relatedness
MM '08 Proceedings of the 16th ACM international conference on Multimedia
Estimating Anomality of the Video Sequences for Surveillance Using 1-Class SVM
IEICE - Transactions on Information and Systems
Motion information for video retrieval
ICME'09 Proceedings of the 2009 IEEE international conference on Multimedia and Expo
Content-based image retrieval by combining genetic algorithm and support vector machine
ICANN'07 Proceedings of the 17th international conference on Artificial neural networks
Multimedia event-based video indexing using time intervals
IEEE Transactions on Multimedia
MPEG-7 visual motion descriptors
IEEE Transactions on Circuits and Systems for Video Technology
Event detection in field sports video using audio-visual features and a support vector Machine
IEEE Transactions on Circuits and Systems for Video Technology
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The spatio-temporal constraints that accompany video data types are one of the unique characteristics of video information. The importance of the temporal constraints has led to recent efforts to incorporate them in video events representation, indexing and retrieval. To support the classification of a given video event, we propose a data-driven model which utilizes the motion information to enhance event classification performance. Kernel-based methods have become popular in multimedia classification tasks. However, in order to use them effectively, several factors that hinder accurate classification results, such as feature subset selection and kernel parameters, must be addressed through the use of heuristic-based techniques. Here, we present a novel approach to enhance the performance of support vector machine based on a search method. The latter relies on the simultaneous optimization of: (i) the feature subset, (ii) the instance subset and, (iii) the SVM kernel function parameters, with genetic algorithms. Experimental results on a collection of sports videos show that this method significantly improves the classification accuracy of conventional SVM based techniques.