Supervised classification for video shot segmentation

Authors:
Yanjun Qi;A. Hauptmann;Ting Liu
Affiliations:
Sch. of Comput. Sci., Carnegie Mellon Univ., Pittsburgh, PA, USA;Sch. of Comput. Sci., Carnegie Mellon Univ., Pittsburgh, PA, USA;Sch. of Comput. Sci., Carnegie Mellon Univ., Pittsburgh, PA, USA
Venue:
ICME '03 Proceedings of the 2003 International Conference on Multimedia and Expo - Volume 1
Year:
2003

Citing 0
Cited 14

Semantic video classification and feature subset selection under context and concept uncertainty

Proceedings of the 4th ACM/IEEE-CS joint conference on Digital libraries
The IOC algorithm: efficient many-class non-parametric classification for high-dimensional data

Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Video segmentation combining similarity analysis and classification

Proceedings of the 12th annual ACM international conference on Multimedia
The influence of cross-validation on video classification performance

MULTIMEDIA '06 Proceedings of the 14th annual ACM international conference on Multimedia
New Algorithms for Efficient High-Dimensional Nonparametric Classification

The Journal of Machine Learning Research
A scalable signature scheme for video authentication

Multimedia Tools and Applications
A robust shot transition detection method based on support vector machine in compressed domain

Pattern Recognition Letters
Incorporating feature hierarchy and boosting to achieve more effective classifier training and concept-oriented video summarization and skimming

ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
An overview of video shot clustering and summarization techniques for mobile applications

MobiMedia '06 Proceedings of the 2nd international conference on Mobile multimedia communications
Scene detection using visual and audio attention

Proceedings of the 2008 Ambi-Sys workshop on Ambient media delivery and interactive television
Video scene segmentation and semantic representation using a novel scheme

Multimedia Tools and Applications
Efficient content analysis engine for visual surveillance network

IEEE Transactions on Circuits and Systems for Video Technology
Episode-constrained cross-validation in video concept retrieval

IEEE Transactions on Multimedia
Computational intelligence in multimedia processing

IWANN'11 Proceedings of the 11th international conference on Artificial neural networks conference on Advances in computational intelligence - Volume Part I

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper, we explore supervised classification methods for video shot segmentation. We transform the temporal segmentation problem into a multi-class categorization issue. This approach provides a uniform framework for using different kinds of features extracted from the video and for detecting various types of shot boundaries. The approach utilizes manual labeled training data and a simple classification structure, which eliminates arbitrary thresholds and achieves more reliable estimation than previous threshold-based methods. Contrastive experiments on 13 videos (/spl sim/4 hours) show excellent performance on the 2001 TREC video track shot classification task in terms of precision and recall.