Adaptive Census Transform: A novel hardware-oriented stereovision algorithm

This paper presents a new hardware-oriented approach for the extraction of disparity maps from stereo images. The proposed method is based on the herein named Adaptive Census Transform that exploits adaptive support weights during the image transformation; the adaptively weighted sum of SADs is then used as the dissimilarity metric. Quality tests show that the proposed method reaches significantly better accuracy than alternative hardware-oriented approaches. To demonstrate the practical hardware feasibility, a specific architecture has been designed and its implementation has been carried out using a single FPGA chip. Such a VLSI implementation allows a frame rate up to 68 fps to be reached for 640 × 480 stereo images, using just 80,000 slices and 32 RAM blocks of a Virtex6 chip.     

Energy efficient and reliable data delivery in urban sensing applications: A performance analysis

Urban sensing is an emerging application field for Wireless Sensor Networks (WSNs), where a number of static sensors is sparsely deployed in an urban area to collect environmental information. Data sensed by each sensor are, then, opportunistically transmitted to Mobile Nodes (MNs) that happen to be in contact. In the considered scenario, communications between MNs and sensors require paradigms with a minimal synchronization between devices, extremely fast and energy efficient, especially at the sensor side. To deal with the above issues, in [1] we proposed a hybrid protocol for data delivery from sensors to MNs, named Hybrid Adaptive Interleaved Data Protocol (HI). By combining Erasure Coding (EC) with an Automatic Repeat reQuest (ARQ) scheme, the proposed protocol maximizes the reliability of communications while minimizing the energy consumed by sensors. In this paper, we present an in-depth analysis of the HI performance. We provide an analytical evaluation by defining a flexible model to derive the probability of data delivery and exploiting it to investigate the performance over a wide range of parameters. Moreover, we perform an experimental study to evaluate the HI effectiveness on real sensor platforms. Specifically, we analyze the impact of resource constraints imposed by sensors on data delivery and provide a careful characterization of its actual consumption of resources.     

Improving the schedulability of soft real-time open dynamic systems: The inheritor is actually a debtor

This paper presents the Clearing Fund Protocol, a three layered protocol designed to schedule soft real-time sets of precedence related tasks with shared resources. These sets are processed in an open dynamic environment. Open because new applications may enter the system at any time and dynamic because the schedulability is tested on-line as tasks request admission. Top-down, the three layers are the Clearing Fund, the Bandwidth Inheritance and two versions of the Constant Bandwidth Server algorithms. Bandwidth Inheritance applies a priority inheritance mechanism to the Constant Bandwidth Server. However, a serious drawback is its unfairness. In fact, a task executing in a server can potentially steal the bandwidth of another server without paying any penalty. The main idea of the Clearing Fund Algorithm is to keep track of processor-time debts contracted by lower priority tasks that block higher priority ones and are executed in the higher priority servers by having inherited the higher priority. The proposed algorithm reduces the undesirable effects of those priority inversions because the blocked task can finish its execution in its own server or in the server of the blocking task, whichever has the nearest deadline. If demanded, debts are paid back in that way. Inheritors are therefore debtors. Moreover, at certain instants in time, all existing debts may be waived and the servers are reset making a clear restart of the system. The Clearing Fund Protocol showed definite better performances when evaluated by simulations against Bandwidth Inheritance, the protocol it tries to improve.     

Mantaining Dynamic Matrices for Fully Dynamic Transitive Closure

In this paper we introduce a general framework for casting fully dynamic transitive closure into the problem of reevaluating polynomials over matrices. With this technique, we improve the best known bounds for fully dynamic transitive closure. In particular, we devise a deterministic algorithm for general directed graphs that achieves O(n ²) amortized time for updates, while preserving unit worst-case cost for queries. In case of deletions only, our algorithm performs updates faster in O(n) amortized time. We observe that fully dynamic transitive closure algorithms with O(1) query time maintain explicitly the transitive closure of the input graph, in order to answer each query with exactly one lookup (on its adjacency matrix). Since an update may change as many as Ω(n ²) entries of this matrix, no better bounds are possible for this class of algorithms. This work has been partially supported by the Sixth Framework Programme of the EU under contract number 507613 (Network of Excellence “EuroNGI: Designing and Engineering of the Next Generation Internet”), and number 001907 (“DELIS: Dynamically Evolving, Large Scale Information Systems”), and by the Italian Ministry of University and Research (Project “ALGO-NEXT: Algorithms for the Next Generation Internet and Web: Methodologies, Design and Experiments”). Portions of this paper have been presented at the 41st Annual Symp. on Foundations of Computer Science, 2000.     

Boosting text segmentation via progressive classification

A novel approach for reconciling tuples stored as free text into an existing attribute schema is proposed. The basic idea is to subject the available text to progressive classification, i.e., a multi-stage classification scheme where, at each intermediate stage, a classifier is learnt that analyzes the textual fragments not reconciled at the end of the previous steps. Classification is accomplished by an ad hoc exploitation of traditional association mining algorithms, and is supported by a data transformation scheme which takes advantage of domain-specific dictionaries/ontologies. A key feature is the capability of progressively enriching the available ontology with the results of the previous stages of classification, thus significantly improving the overall classification accuracy. An extensive experimental evaluation shows the effectiveness of our approach.     

Real-Time Global Illumination for VR Applications

Real-time global illumination in VR systems enhances scene realism by incorporating soft shadows, reflections of objects in the scene, and color bleeding. The Virtual Light Field (VLF) method enables real-time global illumination rendering in VR. The VLF has been integrated with the Extreme VR system for real-time GPU-based rendering in a Cave Automatic Virtual Environment.     

Using visual and text features for direct marketing on multimedia messaging services domain

Traditionally, direct marketing companies have relied on pre-testing to select the best offers to send to their audience. Companies systematically dispatch the offers under consideration to a limited sample of potential buyers, rank them with respect to their performance and, based on this ranking, decide which offers to send to the wider population. Though this pre-testing process is simple and widely used, recently the industry has been under increased pressure to further optimize learning, in particular when facing severe time and learning space constraints. The main contribution of the present work is to demonstrate that direct marketing firms can exploit the information on visual content to optimize the learning phase. This paper proposes a two-phase learning strategy based on a cascade of regression methods that takes advantage of the visual and text features to improve and accelerate the learning process. Experiments in the domain of a commercial Multimedia Messaging Service (MMS) show the effectiveness of the proposed methods and a significant improvement over traditional learning techniques. The proposed approach can be used in any multimedia direct marketing domain in which offers comprise both a visual and text component.

A multimodal semantic location service for intelligent environments: an application for Smart Hospitals

This paper presents semantic models, mechanisms and a service to locate mobile entities in Smart and Intelligent Environments. The key feature of the service is the semantic integration of different positioning systems that not only enables the environment to handle transparently such physical positioning systems, but also to reason on location information coming from different systems and to combine it to obtain higher context information. Indeed, the service relies on the use of ontologies and rules to define a uniform, unambiguous and well-defined model for the location information, independently of the particular positioning system. Moreover, the location service performs logic and reasoning mechanisms to provide both physical and semantic locations of mobile objects and to infer the finest granularity in the case when a mobile object is located by more than one positioning system. Finally, we present an application of the proposed approach to the case of a Smart Hospital.     

System for measuring the coordinates of tire surfaces in transient conditions when rolling over obstacles: description of the system and performance analysis

This paper describes the development of a system for measuring surface coordinates (commonly known as "shape measurements") which is able to give the temporal evolution of the position of the tire sidewall in transient conditions (such as during braking, when there are potholes or when the road surface is uneven) which may or may not be reproducible. The system is based on the well-known technique of projecting and observing structured light using a digital camera with an optical axis which is slanted with respect to the axis of the projector. The transient nature of the phenomenon has led to the development of specific innovative solutions as regards image processing algorithms. This paper briefly describes the components which make up the measuring system and presents the results of the measurements carried out on the drum bench. It then analyses the performance of the measuring system and the sources of uncertainty which led to the development of the system for a specific dynamic application: impact with an obstacle (cleat test). The measuring system guaranteed a measurement uncertainty of 0.28 mm along the Z axis (the axial direction of the tire) with a measurement range of 250(X) x 80(Y) x 25(Z) mm(3), with the tire rolling at a speed of up to 30 km/h.