Synoptic mapping of high-rise buildings in urban areas based on combined shadow analysis and scale space processing

A highly automated methodology is described to map locations and heights of high-rise buildings from single high-resolution multi-spectral satellite imagery. The approach involves preliminary shadow detection using the Tsai colour invariant transform and scale space processing to identify candidate building pixels. Application of shadow-building and shadow length constraints led to mapping of the location and height of building candidate objects. The approach has been applied to a winter SPOT 5 scene of Beijing, China. Tests of buildings in a suburban area indicate that a high detection rate (93%) can be achieved for buildings taller than 28 m. A height estimation accuracy of 20 m has also been met for these buildings.     

Visualization rhetoric: framing effects in narrative visualization

Narrative visualizations combine conventions of communicative and exploratory information visualization to convey an intended story. We demonstrate visualization rhetoric as an analytical framework for understanding how design techniques that prioritize particular interpretations in visualizations that "tell a story" can significantly affect end-user interpretation. We draw a parallel between narrative visualization interpretation and evidence from framing studies in political messaging, decision-making, and literary studies. Devices for understanding the rhetorical nature of narrative information visualizations are presented, informed by the rigorous application of concepts from critical theory, semiotics, journalism, and political theory. We draw attention to how design tactics represent additions or omissions of information at various levels-the data, visual representation, textual annotations, and interactivity-and how visualizations denote and connote phenomena with reference to unstated viewing conventions and codes. Classes of rhetorical techniques identified via a systematic analysis of recent narrative visualizations are presented, and characterized according to their rhetorical contribution to the visualization. We describe how designers and researchers can benefit from the potentially positive aspects of visualization rhetoric in designing engaging, layered narrative visualizations and how our framework can shed light on how a visualization design prioritizes specific interpretations. We identify areas where future inquiry into visualization rhetoric can improve understanding of visualization interpretation.     

Perceptual guidelines for creating rectangular treemaps

Treemaps are space-filling visualizations that make efficient use of limited display space to depict large amounts of hierarchical data. Creating perceptually effective treemaps requires carefully managing a number of design parameters including the aspect ratio and luminance of rectangles. Moreover, treemaps encode values using area, which has been found to be less accurate than judgments of other visual encodings, such as length. We conduct a series of controlled experiments aimed at producing a set of design guidelines for creating effective rectangular treemaps. We find no evidence that luminance affects area judgments, but observe that aspect ratio does have an effect. Specifically, we find that the accuracy of area comparisons suffers when the compared rectangles have extreme aspect ratios or when both are squares. Contrary to common assumptions, the optimal distribution of rectangle aspect ratios within a treemap should include non-squares, but should avoid extremes. We then compare treemaps with hierarchical bar chart displays to identify the data densities at which length-encoded bar charts become less effective than area-encoded treemaps. We report the transition points at which treemaps exhibit judgment accuracy on par with bar charts for both leaf and non-leaf tree nodes. We also find that even at relatively low data densities treemaps result in faster comparisons than bar charts. Based on these results, we present a set of guidelines for the effective use of treemaps and suggest alternate approaches for treemap layout.     

Network virtualization in energy-efficient office environments

The rising costs of energy and world-wide desire to reduce CO₂ emissions has led to an increased concern over the energy efficiency of information and communication technology. Whilst much of this concern has focused on data centres, office environments (and the computing equipment that they contain) have also been identified as a significant consumer of energy. Office environments offer great potential for energy savings, given that computing equipment often remains powered for 24 h per day, and for a large part of this period is underutilised or idle. This paper proposes an energy-efficient office management approach based on resource virtualization, power management, and resource sharing. Evaluations indicate that about 75% energy savings are achievable in office environments without a significant interruption of provided services. A core element of this office management is a peer-to-peer network that interconnects office hosts, achieves addressing and mediation, and manages energy efficiency within the office environment. Several peer-to-peer approaches are suggested and discussed in this paper. Two of the approaches are evaluated, based on a discrete-event simulation.     

Bidding strategies for realistic multi-unit sealed-bid auctions

When autonomous agents decide on their bidding strategies in real world auctions, they have a number of concerns that go beyond the models that are normally analyzed in traditional auction theory. Oftentimes, the agents have budget constraints and the auctions have a reserve price, both of which restrict the bids the agents can place. In addition, their attitude need not be risk-neutral and they may have uncertainty about the value of the goods they are buying. Some of these issues have been examined individually for single-unit sealed-bid auctions. However, in this paper, we extend this analysis to the multi-unit case, and also analyze the multi-unit sealed-bid auctions in which a combination of these issues are present, for unit-demand bidders. This analysis constitutes the main contribution of this paper. We then demonstrate the usefulness in practice of this analysis; we show in simulations that taking into account all these issues allows the bidders to maximize their utility. Furthermore, using this analysis allows a seller to improve her revenue, i.e. by selecting the optimal reserve price and auction format.     

Bubble-sensing: Binding sensing tasks to the physical world

We propose bubble-sensing, a new sensor network abstraction that allows mobile phone users to create a binding between sensing tasks and the physical world at locations of interest, that remains active for a duration set by the user. We envision mobile phones being able to affix sensing task bubbles at places of interest and then receive sensed data as it becomes available in a delay-tolerant fashion, in essence, creating a living documentary of places of interest in the physical world. The system relies on other mobile phones that opportunistically pass through bubble-sensing locations to acquire tasks and do the sensing on behalf of the initiator, and deliver the data to the bubble-sensing server for retrieval by the user who initiated the task.We describe an implementation of the bubble-sensing system using sensor-enabled mobile phones, specifically, Nokia’s N80 and N95 (with GPS, accelerometers, microphone, camera). Task bubbles are maintained at locations through the interaction of “bubble carriers”, which carry the sensing task into the area of interest, and “bubble anchors”, which maintain the task bubble in the area when the bubble carrier is no longer present. In our implementation, bubble carriers and bubble anchors implement a number of simple mobile phone based protocols that refresh the task bubble state as new mobile phones move through the area. Phones communicate using the local Ad-Hoc 802.11g radio to transfer task state and maintain the task in the region of interest. This task bubble state is ephemeral and times out when no bubble carriers or bubble anchors are in the area. Our design is resilient to periods when no mobiles pass through the bubble area and is capable of “reloading” the task into the bubble region. In this paper, we describe the bubble-sensing system and a simple proof-of-concept experiment.     

Raster scan approaches to computer graphics

This text reports on conclusions derived from the building and use of the 85², an elaborate raster scan display system for computer graphics applications. The titled plurality is justified by a generality and by a superset of degrees of freedom in the specific device, all of which no one application warrants and all of which have immense programming implications. The underlying and now generally accepted assumption is that the future of computer graphics is in raster scan technologies. This paper concludes that future implementations ought to be primarily mass memories, rarely scan conversion techniques, and never run-length lists.     

Video fingerprinting using Latent Dirichlet Allocation and facial images

This paper investigates the possibility of extracting latent aspects of a video in order to develop a video fingerprinting framework. Semantic visual information about humans, more specifically face occurrences in video frames, along with a generative probabilistic model, namely the Latent Dirichlet Allocation (LDA), are used for this purpose. The latent variables, namely the video topics are modeled as a mixture of distributions of faces in each video. The method also involves a clustering approach based on Scale Invariant Features Transform (SIFT) for clustering the detected faces and adapts the bag-of-words concept into a bag-of-faces one, in order to ensure exchangeability between topics distributions. Experimental results, on three different data sets, provide low misclassification rates of the order of 2% and false rejection rates of 0%. These rates provide evidence that the proposed method performs very efficiently for video fingerprinting.     

VForce: An environment for portable applications on high performance systems with accelerators

Special Purpose Processors (SPPs), including Field Programmable Gate Arrays (FPGAs) and Graphics Processing Units (GPUs), are increasingly being used to accelerate scientific applications. VForce aims to aid application programmers in using such accelerators with minimal changes in user code. VForce is an extensible middleware framework that enables VSIPL++ (the Vector Signal Image Processing Library extension) programs to transparently use Special Purpose Processors (SPPs) while maintaining portability across platforms with and without SPP hardware. The framework is designed to maintain a VSIPL++-like environment and hide hardware-specific details from the application programmer while preserving performance and productivity. VForce focuses on the interface between application code and accelerator code. The same application code can run in software on a general purpose processor or take advantage of SPPs if they are available. VForce is unique in that it supports calls to both FPGAs and GPUs while requiring no changes in user code. Results on systems with NVIDIA Tesla GPUs and Xilinx FPGAs are presented. This paper describes VForce, illustrates its support for portability, and discusses lessons learned for providing support for different hardware configurations at run time. Key considerations involve global knowledge about the relationship between processing steps for defining application mapping, memory allocation, and task parallelism.