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In this paper, we propose a novel tracking framework, multi-cues spatial pyramid matching (MSPM). Different cues are used to generate a set of probability maps, where the value of each pixel indicates the probability that it belongs to the foreground. Then those probability maps are combined into a single probability map by a weighted linear function. There exist two main contributions. First, a generic...
In this paper, we present a new multiple cues fusion algorithm in visual object tracking, which adaptive adjust the confidence scores based on center areas and surround areas defined on confidence maps. Confidence maps are created where each pixel indicates the probability of that pixel belonging to foreground object or scene background. Center areas and surround areas are used to calculate the confidence...
In this paper we propose a new image event detection method for identifying flood in videos. Traditional image based flood detection is often used in remote sensing and satellite imaging applications. In contrast, the proposed method is applied for retrieval of flood catastrophes in newscast content, which present great variation in flood and background characteristics, depending on the video instance...
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