Machine Learning
Automatic moving object and background separation
Signal Processing - Video segmentation for content-based processing manipulation
Object Tracking Using Deformable Templates
IEEE Transactions on Pattern Analysis and Machine Intelligence
Unsupervised Segmentation of Color-Texture Regions in Images and Video
IEEE Transactions on Pattern Analysis and Machine Intelligence
Support Vector Machines and the Bayes Rule in Classification
Data Mining and Knowledge Discovery
IEEE Transactions on Pattern Analysis and Machine Intelligence
Reducing multiclass to binary: a unifying approach for margin classifiers
The Journal of Machine Learning Research
On the algorithmic implementation of multiclass kernel-based vector machines
The Journal of Machine Learning Research
In Defense of One-Vs-All Classification
The Journal of Machine Learning Research
Statistical Analysis of Some Multi-Category Large Margin Classification Methods
The Journal of Machine Learning Research
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
Solving multiclass learning problems via error-correcting output codes
Journal of Artificial Intelligence Research
Object tracking using the Gabor wavelet transform and the golden section algorithm
IEEE Transactions on Multimedia
Occlusion-adaptive, content-based mesh design and forward tracking
IEEE Transactions on Image Processing
Automatic segmentation of moving objects for video object plane generation
IEEE Transactions on Circuits and Systems for Video Technology
Unsupervised video segmentation based on watersheds and temporal tracking
IEEE Transactions on Circuits and Systems for Video Technology
Semiautomatic segmentation and tracking of semantic video objects
IEEE Transactions on Circuits and Systems for Video Technology
Hierarchical 2-D mesh representation, tracking, and compression for object-based video
IEEE Transactions on Circuits and Systems for Video Technology
IEEE Transactions on Circuits and Systems for Video Technology
Semantic video object extraction using four-band watershed and partition lattice operators
IEEE Transactions on Circuits and Systems for Video Technology
Fast and automatic video object segmentation and tracking for content-based applications
IEEE Transactions on Circuits and Systems for Video Technology
Efficient moving object segmentation algorithm using background registration technique
IEEE Transactions on Circuits and Systems for Video Technology
Automatic segmentation of moving objects in video sequences: a region labeling approach
IEEE Transactions on Circuits and Systems for Video Technology
Semiautomatic video object segmentation using VSnakes
IEEE Transactions on Circuits and Systems for Video Technology
Video object segmentation and tracking using ψ-learning classification
IEEE Transactions on Circuits and Systems for Video Technology
A comparison of methods for multiclass support vector machines
IEEE Transactions on Neural Networks
IEEE Transactions on Neural Networks
Margin and domain integrated classification
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
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Video object (VO) extraction is of great importance in multimedia processing. In recent years approaches have been proposed to deal with VO extraction as a classification problem. This type of methods calls for state-of-the-art classifiers because the performance is directly related to the accuracy of classification. Promising results have been reported for single object extraction using support vector machines (SVM) and its extensions. Multiple object extraction, on the other hand, still imposes great difficulty as multi-category classification is an ongoing research topic in machine learning. This paper introduces a new scheme of multi-category learning for multiple VO extraction, and demonstrates its effectiveness and advantages by experiments.