Outlier percentage estimation for shape‐ and parameter‐independent outlier detection

Shape Based Outlier Detection in SLIC Superpixels

FP-outlier: Frequent pattern based outlier detection

An outlier in a dataset is an observation or a point that is considerably dissimilar to or inconsistent with the remainder of the data. Detection of such outliers is important for many applications and has recently attracted much attention in the data mining research community. In this paper, we present a new method to detect outliers by discovering frequent patterns (or frequent itemsets) from...

Shape outlier detection and visualization for functional data: the outliergram.

We propose a new method to visualize and detect shape outliers in samples of curves. In functional data analysis, we observe curves defined over a given real interval and shape outliers may be defined as those curves that exhibit a different shape from the rest of the sample. Whereas magnitude outliers, that is, curves that lie outside the range of the majority of the data, are in general easy ...

Shape Outlier Detection Using Pose Preserving Dynamic Shape Models

In this paper, we introduce a framework for shape outlier, like carrying object, detection in different people from different views using pose preserving dynamic shape models. We model dynamic human shape deformations in different people using kinematics manifold embedding and decomposition of nonlinear mapping using kernel map and multilinear analysis. The generative model supports pose-preser...

A Unified Subspace Outlier Ensemble Framework for Outlier Detection

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