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We propose a simple information-theoretic clustering approach based on maximizing the mutual information I(\sfx,y) between the unknown cluster labels y and the training patterns \sfx with respect to parameters of specifically constrained encoding dis ...
A system is presented to detect and match any objects with mobile cameras collaborating with fixed cameras observing the same scene. No training data is needed. Various object descriptors are studied based on grids of region descriptors. Region descriptors ...
This article explores the feasibility of a market-ready, mo- bile pattern recognition system based on the latest findings in the field of object recognition and currently available hardware and network technology. More precisely, an innovative, mobile muse ...
In this paper we propose to use clustering methods for automatic counting of pedestrians in video sequences. As input, we consider the output of those detection/ tracking systems that overestimate the number of targets. Clustering techniques are applied to ...
One of the shortcomings of the existing clustering methods is their problems dealing with different shape and size clusters. On the other hand, most of these methods are designed for especial cluster types or have good performance dealing with particular s ...
This thesis presents an algorithm for face tracking in video sequences. We investigate the application of affine invariant, local features for face tracking under random poses and expressions. In order to capture as much as possible of the facial variabili ...
In this paper we propose an approach to count the number of pedestrians, given a trajectory data set provided by a tracking system. The tracking process itself is treated as a black box providing us the input data. The idea is to apply a hierarchical clust ...
This work presents document clustering experiments performed over noisy texts (i.e. text that have been extracted through an automatic process like speech or character recognition). The effect of recognition errors on different clustering techniques is mea ...
We propose a general approach for the design of 2D feature detectors from a class of steerable functions based on the optimization of a Canny-like criterion. In contrast with previous computational designs, our approach is truly 2D and provides filters tha ...
In this paper, we present a novel speaker segmentation and clustering algorithm. The algorithm automatically performs both speaker segmentation and clustering without any prior knowledge of the identities or the number of speakers. Advantages of this algor ...
