Ahmed Abdelkader

Analysis of a Device-Free Passive Tracking System in Typical Wireless Environments

Device-free Passive (DfP) localization is a new concept in location determination where the tracked entity does not carry any device nor participate actively in the localization process. A DfP system operates by processing the received physical signal of a wireless transmitter at one or more monitoring points. The previously introduced DfP system was shown to enable the tracking of a single intruder with high accuracy in a highly controlled WLAN environment. In this paper, we propose and analyze different algorithms for DfP tracking in a typical indoor WLAN environment, rich in multipath. We also study the effect of the temporal and spatial changes in the environment on the accuracy of the system. In addition, we evaluate the effect of the different configurations of the wireless equipment placement on the DfP localization accuracy. Our results show that our proposed techniques can accurately track the user in typical environments, thus enabling a large number of DfP applications.

Argus: realistic target coverage by drones

Low-cost mini-drones with advanced sensing and maneuverability enable a new class of intelligent visual sensing systems. This potential motivated several research efforts to employ drones as standalone surveillance systems or to assist legacy deployments. However, several fundamental challenges remain unsolved including: 1) Adequate coverage of sizable targets; 2) Target orientation that render coverage effective only from certain directions; 3) Occlusion by elements in the environment, including other targets.In this paper, we present Argus, a system that provides visual coverage of wide and oriented targets, using camera-mounted drones, taking into account the challenges stated above. Argus relies on a geometric model that captures both target shapes and coverage constraints. With drones being the scarcest resource in Argus, we study the problem of minimizing the number of drones required to cover a set of such targets and derive a best-possible approximation algorithm. Building upon that, we present a sampling heuristic that performs favorably, while running up to 100x faster compared to the approximation algorithm. We implement a complete prototype of Argus to demonstrate and evaluate the proposed coverage algorithms within a fully autonomous surveillance system. Finally, we evaluate the proposed algorithms via simulations to compare their performance at scale under various conditions.

Brands in NewsStand: spatio-temporal browsing of business news

The NewsStand system enables the use of a map query interface to retrieve news articles associated with the principal locations that they mention collected as a result of monitoring the output of over 10,000 RSS news feeds, made available within minutes of publication. NewsStand has been enhanced to allow using the map query interface to access other information associated with the articles such as photos and videos, as well as names of people and diseases mentioned in these articles. Here we report on our efforts to enhance NewsStand to display the names of brands and to the articles mentioning them. The challenges in identifying interesting brand mentions are discussed.

Angular Heuristics for Coverage Maximization in Multi-camera Surveillance

Multiple cameras are used to track targets moving amongst obstacles. Surveillance video streamed from a top-view camera is processed to control the orientation of multiple pan-tilt-zoom cameras to cover as many targets as possible at high resolutions. The problem of maximizing the number of covered targets with a set of cameras has been shown to be computationally expensive and hence, several approximations have been suggested in the literature. We develop our own ones, compare them to some existing approaches by extensive simulation and show their superiority. Our new heuristics make an attempt at continuous panning that is needed when moving to real world experimentation to achieve seamless target tracking.

2048 Without New Tiles Is Still Hard.

We study the computational complexity of a variant of the popular 2048 game in which no new tiles are generated after each move. As usual, instances are defined on rectangular boards of arbitrary size. We consider the natural decision problems of achieving a given constant tile value, score or number of moves. We also consider approximating the maximum achievable value for these three objectives. We prove all these problems are NP-hard by a reduction from 3SAT. Furthermore, we consider potential extensions of these results to a similar variant of the Threes! game. To this end, we report on a peculiar motion pattern, that is not possible in 2048, which we found much harder to control by similar board designs.

A Constrained Resampling Strategy for Mesh Improvement

In many geometry processing applications, it is required to improve an initial mesh in terms of multiple quality objectives. Despite the availability of several mesh generation algorithms with provable guarantees, such generated meshes may only satisfy a subset of the objectives. The conflicting nature of such objectives makes it challenging to establish similar guarantees for each combination, e.g., angle bounds and vertex count. In this paper, we describe a versatile strategy for mesh improvement by interpreting quality objectives as spatial constraints on resampling and develop a toolbox of local operators to improve the mesh while preserving desirable properties. Our strategy judiciously combines smoothing and transformation techniques allowing increased flexibility to practically achieve multiple objectives simultaneously. We apply our strategy to both planar and surface meshes demonstrating how to simplify Delaunay meshes while preserving element quality, eliminate all obtuse angles in a complex mesh, and maximize the shortest edge length in a Voronoi tessellation far better than the state‐of‐the‐art.

Sampling Conditions for Conforming Voronoi Meshing by the VoroCrust Algorithm

We study the problem of decomposing a volume bounded by a smooth surface into a collection of Voronoi cells. Unlike the dual problem of conforming Delaunay meshing, a principled solution to this problem for generic smooth surfaces remained elusive. VoroCrust leverages ideas from α-shapes and the power crust algorithm to produce unweighted Voronoi cells conforming to the surface, yielding the first provably-correct algorithm for this problem. Given an ϵ-sample on the bounding surface, with a weak σ-sparsity condition, we work with the balls of radius δ times the local feature size centered at each sample. The corners of this union of balls are the Voronoi sites, on both sides of the surface. The facets common to cells on opposite sides reconstruct the surface. For appropriate values of ϵ, σ and δ, we prove that the surface reconstruction is isotopic to the bounding surface. With the surface protected, the enclosed volume can be further decomposed into an isotopic volume mesh of fat Voronoi cells by generating a bounded number of sites in its interior. Compared to state-of-the-art methods based on clipping, VoroCrust cells are full Voronoi cells, with convexity and fatness guarantees. Compared to the power crust algorithm, VoroCrust cells are not filtered, are unweighted, and offer greater flexibility in meshing the enclosed volume by either structured grids or random samples.

VoroCrust Illustrated: Theory and Challenges (Multimedia Exposition).

Over the past decade, polyhedral meshing has been gaining popularity as a better alternative to tetrahedral meshing in certain applications. Within the class of polyhedral elements, Voronoi cells are particularly attractive thanks to their special geometric structure. What has been missing so far is a Voronoi mesher that is sufficiently robust to run automatically on complex models. In this video, we illustrate the main ideas behind the VoroCrust algorithm, highlighting both the theoretical guarantees and the practical challenges imposed by realistic inputs.

Economical Delone Sets for Approximating Convex Bodies

Convex bodies are ubiquitous in computational geometry and optimization theory. The high combinatorial complexity of multidimensional convex polytopes has motivated the development of algorithms and data structures for approximate representations. This paper demonstrates an intriguing connection between convex approximation and the classical concept of Delone sets from the theory of metric spaces. It shows that with the help of a classical structure from convexity theory, called a Macbeath region, it is possible to construct an epsilon-approximation of any convex body as the union of O(1/epsilon^{(d-1)/2}) ellipsoids, where the center points of these ellipsoids form a Delone set in the Hilbert metric associated with the convex body. Furthermore, a hierarchy of such approximations yields a data structure that answers epsilon-approximate polytope membership queries in O(log (1/epsilon)) time. This matches the best asymptotic results for this problem, by a data structure that both is simpler and arguably more elegant.

Recovering visibility and dodging obstacles in pursuit-evasion games

Pursuit-evasion games encompass a wide range of planning problems with a variety of constraints on the motion of agents. We study the visibility-based variant where a pursuer is required to keep an evader in sight, while the evader is assumed to attempt to hide as soon as possible. This is particularly relevant in the context of video games where non-player characters of varying skill levels frequently chase after and attack the player. In this paper, we show that a simple dual formulation of the problem can be integrated into the traditional model to derive optimal strategies that tolerate interruptions in visibility resulting from motion among obstacles. Furthermore, using the enhanced model we propose a competitive procedure to maintain the optimal strategies in a dynamic environment where obstacles can change both shape and location. We prove the correctness of our algorithms and present results for different maps.