We present a novel reversible (lossless) data hiding (embedding) technique, which enables the exact recovery of the original host signal upon extraction of the embedded informatio...
Mehmet Utku Celik, Gaurav Sharma, Eli Saber, A. Mu...
This paper deals with the matching of geometric objects including points, curves, surfaces, and subvolumes using implicit object representations in both linear and non-linear sett...
Alex D. Leow, Henry S. C. Huang, Hillary Protas, L...
A wide number of algorithmsfor surjtiacesegmentationin range images have been recentlyproposed characterizedby different approaches (edgefilling, regiongrowing, ...), different su...
Luigi Cinque, Stefano Levialdi, Gianluca Pignalber...
In this paper we analyze the most popular evaluation metrics for separate-and-conquer rule learning algorithms. Our results show that all commonly used heuristics, including accur...
In this paper, we propose a novel variational framework for the reconstruction of dynamic objects from sparse and noisy tomographic data. Using an object-based scene model, we dev...