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Video analysis of athlete action is becoming an important tool for sports training, since it has no intervention to the athlete and there are abundant archived data it can exploit. In this paper we present our work on the automatic analysis of complex individual actions in diving video aiming at providing biometric measurements and visual tools for coaching assistant and performance improving. The...
For conveniently navigating and editing the news programs, it is very important to segment the video into meaningful units. The effective indexing of news videos can be fulfilled by the anchorperson shot because it is an indicator which denotes the occurrence of upcoming news stories. The paper presents a novel anchorperson detection algorithm based on spatio-temporal slice (STS). With STSpattern...
Nowadays, automatic detection of highlights for movies is indispensable for video management and browsing. In this paper, we specifically present the formulation of human attention model and its application for action movie analysis. Depending on the relationship between stimuli in both visual and audio modalities and the change of human attention, we construct the visual and audio attention sub-models...
This paper proposes a global motion estimation (GME) method based on a compact motion model to predict the changes between the successive frames in panoramic video coding. Compared with other complex motion models, the compact motion model uses only three motion parameters to describe the translational motion and non-translational motion (i.e. zooming) accurately in GME. Experimental results show...
We propose an improved fusion method used in high level feature extraction at TRECVID - average precision based Adaboost (AP-based Adaboost). The AP-based weighting scheme makes use of both the weight and the rank of each sample that all have contribution to the final average precision. The weighting scheme along with the more adaptive formulae modified in our method makes it outperform the standard...
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