In this paper the segmentation of a meeting into meeting events is investigated as well as the recognition of the detected segments. First the classification of a meeting event is...
Detection of objects is in general a computationally demanding task. To simplify the problem it is of interest to utilize contextual information and perform a staggered recognitio...
By treating projectors as pin-hole cameras, we show it is possible to calibrate the projectors of a casually-aligned, multi-projector display wall using the principles of planar a...
This paper introduces a novel measure for object convexity using the recently introduced Multi-Scale Autoconvolution transform. The proposed measure is computationally efficient a...
This paper assesses the recently proposed affine invariant image transform called Multi-Scale Autoconvolution (MSA) in some practical object classification problems. A classificat...
This paper describes a method for curvature dependant Skeletonisation in grey-scale images. We commence from a magnetostatic analogy, where the tangential edge flow (the cross pro...
Feature subset selection, applied as a pre-processing step to machine learning, is valuable in dimensionality reduction, eliminating irrelevant data and improving classifier perfo...
This paper presents an application of the general sample-to-object approach to the problem of invariant image classification. The approach results in defining new SVM kernels base...
When comparing different methods for face detection or localization, one realizes that just simply comparing the reported results is misleading as, even if the results are reporte...