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In this paper, we present a novel scene change detection algorithm for mobile camera platforms. Our approach integrates sparse 3D scene background modelling and dense 2D image background modelling into a unified framework. The 3D scene background modelling identifies inconsistent clusters over time in a set of 3D cloud points as the scene changes. The 2D image background modelling further confirms...
The most successful approaches to video understanding and video matching use local spatio-temporal features as a sparse representation for video content. Until now, no principled evaluation of these features has been done. We present FeEval, a dataset for the evaluation of such features. For the first time, this dataset allows for a systematic measurement of the stability and the invariance of local...
This paper focuses on a practical technique for mosaicking video frames captured by thermal infrared (IR) cameras flown on a small Unmanned Aerial Vehicle (UAV). A Scale Invariant Feature Transform (SIFT) algorithm is used for detecting the matching feature points. Then, the k-d tree and RANSAC algorithms are used to find the best match as well as to eliminate the outliers. We propose a novel method...
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