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One major problem in pattern recognition is estimating probability density functions. Unfortunately, parametric techniques rely on an arbitrary assumption on the form of the underlying, unknown density function. On the other hand, nonparametric techniques, such as the popular kn-nearest neighbor (not to be confused with the k-nearest neighbor classification algorithm), allow to remove such an assumption...
Background subtraction is a crucial step in many automatic video content analysis applications. While numerous acceptable techniques have been proposed so far for background extraction, there is still a need to produce more efficient algorithms in terms of adaptability to multiple environments, noise resilience, and computation efficiency. In this paper, we present a powerful method for background...
In this contribution we introduce a clustering scheme based on mode boundary detection procedures. Modes are characterized as compact regions of the data space with higher densities than their surrounding. A mode boundary as defined in this approach is an area of large local changes in the probability density functions. Examples of the performance of the clustering based on the so-obtained mode boundaries...
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