This paper introduces a multilinear principal component analysis (MPCA) framework for tensor object feature extraction. Objects of interest in many computer vision and pattern rec...
Haiping Lu, Konstantinos N. Plataniotis, Anastasio...
We present a 3D, probabilistic object-surface model, along with mechanisms for probabilistically integrating unregistered 2.5D views into the model, and for segmenting model instan...
This paper addresses the problem of recognizing objects in large image databases. The method is based on local characteristics which are invariant to simzlarity transformations in...
Effective testing involves preparing test oracles and test cases, two activities which are too tedious to be effectively performed by humans, yet for the most part remain manual. T...
Bertrand Meyer, Ilinca Ciupa, Andreas Leitner, Lis...
This article investigates the growing complexity and connectivity between two former separated interaction spaces – the real and the virtual world. It is our attempt to augment ...