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SVM is one of the state-of-the-art techniques for image and video classification. When multiple kernels are available, the recently introduced multiple kernel SVM (MK-SVM) learns an optimal linear combination of the kernels, providing a new method for information fusion. In this paper we study how the behaviour of MK-SVM is affected by the norm used to regularise the kernel weights to be learnt. Through...
A new approach for interactive video browsing is described. The novelty of the proposed approach is the flexible concept of interactive navigation summaries. Similar to time sliders, commonly used with standard soft video players, navigation summaries allow random access to a video. In addition, they also provide abstract visualizations of the content at a user-defined level of detail and, thus, quickly...
Objects like field lines and players are important for semantic analysis in soccer video. In this paper, we propose effective methods for field lines and players detection and recognition. Regions of field lines and players are first segmented from shot of wide angle view. Gray value top-hat transform is then performed on the segmented region to detect field lines. Mid-lines, end-lines and penalty-lines...
In this paper we present a new approach for tracking movements of human body in dynamic scenes. The body is characterized by a set of points of interest (PI) issued from Harris corner detector where every one is characterized by its local appearance and its position in each frame of the video sequence. Tracking is achieved by template matching between PI in a pair of consecutive frames in the sequence...
The excessively long reviewing times for diagnosis of capsule endoscopy present a clinical problem. A new method, ldquoadaptive speedrdquo, which automatically controls display rates of the video capsule endoscopy images, was proposed to address the problem. In this paper, we investigate the effectiveness of this method versus a standard-view using the existing system. The main activities of examining...
In this paper, we propose a novel hierarchical framework for soccer (football) video classification. Unlike most existing video classification approaches, which focus on shot detection followed by classification based on clustering using shot aggregation, the proposed scheme perform a top-down video scene classification which avoids shot clustering. This improves the classification accuracy and also...
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