This paper introduces an efficient 3D segmentation concept, which is based on extending the well-known Maximally Stable Extremal Region (MSER) detector to the third dimension. The...
We propose an object detection method using particle filters. Our approach estimates the probability of object presence in the current image given the history of observations up t...
The quantization parameter (QP) has a very important impact on the compression rate in H.264. In this paper we show that in order to achieve efficient rate-control coding a good e...
Laser based people tracking systems have been developed for mobile robotic or intelligent surveillance areas. Existing systems rely on laser point clustering to extract object loc...
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...