Images obtained with catadioptric sensors contain significant deformations which prevent the direct use of classical image treatments. Thus, Markov Random Fields (MRF) whose usefu...
In this paper, a novel unsupervised approach for the segmentation of unorganized 3D points sets is proposed. The method derives by the mean shift clustering paradigm devoted to se...
Marco Cristani, Umberto Castellani, Vittorio Murin...
This paper restates the shape from shading problem regarding both surface modeling and optimization. We combine the use of a B-spline as 3D model for the scene surface and the use...
We introduce the `No Panacea Theorem' for classifier combination in the two-classifier, two-class case. It states that if the combination function is continuous and diverse, ...
We propose a criterion, called `maximal redundancy', for onset detection in time series. The concept redundancy is adopted from information theory and indicates how well a si...
K-Nearest Neighbors relies on the definition of a global metric. In contrast, Discriminant Adaptive Nearest Neighbor (DANN) computes a different metric at each query point based o...
A new method is presented for detecting planar rotational symmetry under affine projection. The method can deal with partial occlusion and is able to detect multiple rotationally ...
2D projection imaging is a widely used procedure for vessel visualization. For the subsequent analysis of the vasculature, precise measurements of e.g. vessel area, vessel length ...
In this paper, we propose a new data reduction algorithm that iteratively selects some samples and ignores others that can be absorbed, or represented, by those selected. This alg...
Most object recognition systems require large databases of real images for classifier training. To collect real images for this purpose is a difficult and expensive process. This ...