Abstract. Recently, new segmentation models based on local information have emerged. They combine local statistics of the regions along the contour (inside and outside) to drive th...
This paper addresses the important tradeoff between privacy and learnability, when designing algorithms for learning from private databases. We focus on privacy-preserving logisti...
We present a novel method for vision-based recovery of three-dimensional structures through simultaneous model reconstruction and camera position tracking from monocular images. O...
Oliver Ruepp, Darius Burschka, Robert Bauernschmit...
In this paper we propose the Possibilistic C-Means in Feature Space and the One-Cluster Possibilistic C-Means in Feature Space algorithms which are kernel methods for clustering in...
Maurizio Filippone, Francesco Masulli, Stefano Rov...
In this paper, a novel feature selection algorithm for object tracking is proposed. This algorithm performs more robust than the previous works by taking the correlation between f...