Artificial Intelligence
A Shortest Path Representation for Video Summarisation
ICIAP '03 Proceedings of the 12th International Conference on Image Analysis and Processing
Sports video categorizing method using camera motion parameters
ICME '03 Proceedings of the 2003 International Conference on Multimedia and Expo - Volume 1
Using camera motion to identify types of American football plays
ICME '03 Proceedings of the 2003 International Conference on Multimedia and Expo - Volume 1
A Visual Attention Based Region-of-Interest Determination Framework for Video Sequences*
IEICE - Transactions on Information and Systems
IEEE Transactions on Multimedia
A unified approach to shot change detection and camera motion characterization
IEEE Transactions on Circuits and Systems for Video Technology
Rapid estimation of camera motion from compressed video with application to video annotation
IEEE Transactions on Circuits and Systems for Video Technology
An evidential fusion architecture for people surveillance in wide open areas
HAIS'11 Proceedings of the 6th international conference on Hybrid artificial intelligent systems - Volume Part I
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We propose in this paper an original method of camera motion classification based on Transferable Belief Model (TBM). It consists in locating in a video the motions of translation and zoom, and the absence of camera motion (i.e static camera). The classification process is based on a rule-based system that is divided into three stages. From a parametric motion model, the first stage consists in combining data to obtain frame-level belief masses on camera motions. To ensure the temporal coherence of motions, a filtering of belief masses according to TBM is achieved. The second stage carries out a separation between static and dynamic frames. In the third stage, a temporal integration allows the motion to be studied on a set of frames and to preserve only those with significant magnitude and duration. Then, a more detailed description of each motion is given. Experimental results obtained show the effectiveness of the method.