Alexander N. Dolia

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Minimum volume covering ellipsoid estimation is important in areas such as systems identification, control, video tracking, sensor management, and novelty detection. It is well known that finding the minimum volume covering ellipsoid (MVCE) reduces to a convex optimisation problem. We propose a regularised version of the MVCE problem, and derive its dual(More)
Ellipsoid estimation is important in many practical areas such as control, system identification, visual/audio tracking, experimental design, data mining, robust statistics and statistical outlier or novelty detection. A new method, called Kernel Minimum Volume Covering Ellipsoid (KMVCE) estimation, that finds an ellipsoid in a kernel-defined feature space(More)
A description of an approach to primary local image recognition is given. The motivation for its application and its characteristics are discussed. Then a method for correction of misclassifications that occur in primary local image recognition is proposed. This method uses a graph-based estimation technique that uses information contained in supplementary(More)
When counterphase spatio-temporal flicker is presented to the left and right eye continuous directional motion can be perceived. Here, we investigate whether this type of dichoptic motion can be observed at different depth planes. Four observers indicated direction of motion for dichoptic motion stimuli, presented in a context containing crossed and(More)
An estimation method for correcting misclassifications in signal and image processing is presented. The method is based on the use of context-based (temporal or spatial) information in a sliding-window fashion. The classes can be purely nominal, that is, an ordering of the classes is not required. Themethod employs nonlinear operations based on class(More)
In this paper we study the active sensor management problem using continuous optimal experimental design (OED) framework. This task comprises the determination of allocation for a limited number of sensors over the spatial domain and the number of repetitive measurements in these locations in order to improve the overall system performance. We present a(More)
We propose a new adaptive novelty detection based algorithm for the primary local recognition of images corrupted by multiplicative/additive and impulse noise. The purpose of primary local recognition or low level analysis such as segmentation, small object and outlier detection is to provide a representation which could be potentially used e.g. in context(More)
Ellipsoid estimation is an issue of primary importance in many practical areas such as control, system identification, visual/audio tracking, experimental design, data mining, robust statistics and novelty/outlier detection. This paper presents a new method of kernel information matrix ellipsoid estimation (KIMEE) that finds an ellipsoid in a kernel defined(More)
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