Learning typical motion patterns or activities from videos of crowded scenes is an important visual surveillance problem. To detect typical motion patterns in crowded scenarios, w...
We present an algorithm for the segmentation of the liver in 2-D computed tomography slice images. The basis for our algorithm is an implicit active shape model. In order to detec...
We address the problem of automatic object classification for traffic scene surveillance, which is very challenging for the low resolution videos, large intraclass variations and ...
We present a method for merging multiple partitions into a single partition, by minimising the ratio of pairwise agreements and contradictions between the equivalence relations cor...
We outline an incremental learning algorithm designed for nonstationary environments where the underlying data distribution changes over time. With each dataset drawn from a new e...
Matthew T. Karnick, Michael Muhlbaier, Robi Polika...
In this paper, we present optimal in time algorithms to compute the distance transform, the reverse distance transform and the discrete medial axis on digital objects embedded on ...
This paper presents a method for camera pose tracking that uses a partial knowledge about the scene. The method is based on monocular vision Simultaneous Localization And Mapping ...
We propose a novel set of medial feature interest points based on gradient vector flow (GVF) fields [18]. We exploit the long ranging GVF fields for symmetry estimation by calcula...
Due to the increased need for security and surveillance, PTZ cameras are now being widely used in many domains. Therefore, it is very important for the applications like video mos...