Guido Proietti

Bio: Guido Proietti is an academic researcher from University of L'Aquila. The author has contributed to research in topics: Spanning tree & Shortest path problem. The author has an hindex of 21, co-authored 156 publications receiving 1742 citations. Previous affiliations of Guido Proietti include University of Rome Tor Vergata & National Research Council.

Image indexing and retrieval based on human perceptual color clustering

Abstract: We propose a new image retrieval method based on human perceptual clustering of color images. This color clustering produces for each image a small set of representative colors which captures the color properties of the image, and a small set of sizable contiguous regions which captures the spatial/geometrical properties of the image. The proposed method outperforms the traditional histogram and its improved methods not only with its richer image retrieval capabilities which cover a wider spectrum of user requirements, but also with its powerful indexing scheme which is essential to cater for large scale image databases.

Swapping a Failing Edge of a Single Source Shortest Paths Tree Is Good and Fast

Abstract: . Let G=(V,E) be a 2-edge connected, undirected and nonnegatively weighted graph, and let S(r) be a single source shortest paths tree (SPT) of G rooted at r ∈ V . Whenever an edge e in S(r) fails, we are interested in reconnecting the nodes now disconnected from the root by means of a single edge e' crossing the cut created by the removal of e . Such an edge e' is named a swap edge for e . Let S e/e' (r) be the swap tree (no longer an SPT, in general) obtained by swapping e with e' , and let S e be the set of all possible swap trees with respect to e . Let F be a function defined over S e that expresses some feature of a swap tree, such as the average length of a path from the root r to all the nodes below edge e , or the maximum length, or one of many others. A best swap edge for e with respect to F is a swap edge f such that F(S e/f (r)) is minimum. In this paper we present efficient algorithms for the problem of finding a best swap edge, for each edge e of S(r) , with respect to several objectives. Our work is motivated by a scenario in which individual connections in a communication network suffer transient failures. As a consequence of an edge failure, the shortest paths to all the nodes below the failed edge might completely change, and it might be desirable to avoid an expensive switch to a new SPT, because the failure is only temporary. As an aside, what we get is not even far from a new SPT: our analysis shows that the trees obtained from the swapping have features very similar to those of the corresponding SPTs rebuilt from scratch.

On the Approximability of TSP on Local Modifications of Optimally Solved Instances

Abstract: Given an instance of TSP together with an optimal solution, we consider the scenario in which this instance is modified locally, where a local modification consists in the alteration of the weight of a single edge. More generally, for a problem U , let LM- U (local-modification- U ) denote the same problem as U , but in LM- U , we are also given an optimal solution to an instance from which the input instance can be derived by a local modification. The question is how to exploit this additional knowledge, i.e., how to devise better algorithms for LM- U than for U . Note that this need not be possible in all cases: The general problem of LM-TSP is as hard as TSP itself, i.e., unless P=NP, there is no polynomial-time p(n)-approximation algorithm for LM-TSP for any polynomial p. Moreover, LM-TSP where inputs must satisfy the β-triangle inequality (LM-Δ β -TSP) remains NP-hard for all β>½. However, for LM-Δ-TSP (i.e., metric LM-TSP), we will present an efficient 1.4-approximation algorithm. In other words, the additional information enables us to do better than if we simply used Christofides' algorithm for the modified input. Similarly, for all 1<β<3.34899, we achieve a better approximation ratio for LM-Δ-TSP than for Δ β -TSP. For ½≤β<1, we show how to obtain an approximation ratio arbitrarily close to 1, for sufficiently large input graphs.

Random graphs

Abstract: We will review some of the major results in random graphs and some of the more challenging open problems. We will cover algorithmic and structural questions. We will touch on newer models, including those related to the WWW.

Triangulating a simple polygon in linear time

Abstract: We give a deterministic algorithm for triangulating a simple polygon in linear time. The basic strategy is to build a coarse approximation of a triangulation in a bottom-up phase and then use the information computed along the way to refine the triangulation in a top-down phase. The main tools used are the polygon-cutting theorem, which provides us with a balancing scheme, and the planar separator theorem, whose role is essential in the discovery of new diagonals. Only elementary data structures are required by the algorithm. In particular, no dynamic search trees, of our algorithm.

Multimedia content analysis-using both audio and visual clues

Abstract: Multimedia content analysis refers to the computerized understanding of the semantic meanings of a multimedia document, such as a video sequence with an accompanying audio track. With a multimedia document, its semantics are embedded in multiple forms that are usually complimentary of each other, Therefore, it is necessary to analyze all types of data: image frames, sound tracks, texts that can be extracted from image frames, and spoken words that can be deciphered from the audio track. This usually involves segmenting the document into semantically meaningful units, classifying each unit into a predefined scene type, and indexing and summarizing the document for efficient retrieval and browsing. We review advances in using audio and visual information jointly for accomplishing the above tasks. We describe audio and visual features that can effectively characterize scene content, present selected algorithms for segmentation and classification, and review some testbed systems for video archiving and retrieval. We also describe audio and visual descriptors and description schemes that are being considered by the MPEG-7 standard for multimedia content description.

Discrete Applied Mathematics

Abstract: : Significant progress has been made with solution of location problems and in preprocessing and decomposition for discrete optimization. There has also been research on the application of techniques from combinational optimization to nonlinear problems.