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Extracting the motion patterns from videos is a basic task in video surveillance and has become an active research area. In this paper, we propose a novel approach for discovering motion patterns in a scene observed by one or two cameras. The chaos theory is employed to compute the chaotic invariant features (CIFs) after obtaining all the trajectories. The CIFs and other features are combined to a...
The exponential growth of the size of the search space has always been an obstacle to POMDP planning. Heuristics are often used to reduce the search space size and improve computational efficiency. As the advantage of the feature of POMDP problems should be taken into deeper consideration, we analyze the clustering feature of reachable space of POMDP problems and apply policy iteration based on this...
Nowadays in order to process and store many kinds of multimedia data, the storage capability of memory has grown greatly. Moreover the widespread use of mobile devices and cloud computing has made criminal investigators often face a lot of memory dumps. They have to deal with a large quantity of memory data and complex OS data structures which they have little knowledge of. How to analyze memory evidence...
Although many methods of refining initialization have appeared, the sensitivity of K-Means to initial centers is still an obstacle in applications. In this paper, we investigate a new class of clustering algorithm, K-Alpha Means (KAM), which is insensitive to the initial centers. With K-Harmonic Means as a special case, KAM dynamically weights data points during iteratively updating centers, which...
In this paper, we propose a new synthetic aperture radar (SAR) image segmentation scheme. Firstly, the SAR image is over-segmented using the mean shift (MS) algorithm while the original image discontinuity characteristics are preserved. Secondly, we propose a novel method to estimates the probability density function of each node on region adjacency graph (RAG) using kernel density estimation (KDE)...
This paper introduces a relational graph representation method using the angle between spectral coefficient vectors. A relational graph clustering system builds on this presentation method. The system adopts fuzzy C-mean (FCM) as clustering algorithm. FCM exerts on the pattern space which embedded by locality preserving projections (LPP). The pattern space obtains from Laplacian matrix constructed...
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