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Mike Cammarano

dblp:64/5637 · DBLP profile ↗
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5ranked-venue papers
1as first author
0since 2021 · last 2009
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Graphics, computer vision, multimedia, augmented reality and games · 4 · 1 first-authorDatabases, data management, data science and information retrieval · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer graphics and multimedia
5 papers
Visualization and visual analytics · 67% Rendering · 33%
Databases, data mining, and information retrieval
3 papers
Knowledge graphs · 54% Data models and query languages · 46%

Topics — the 11 heaviest of 13, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Visualization and visual analytics
interactive data exploration
0.222009
Vispedia: on-demand data integration for interactive visualization and exploration · SIGMOD Conference 2009
Vispedia: Interactive Visual Exploration of Wikipedia Data via Search-Based Integration · IEEE Trans. Vis. Comput. Graph. 2008
Visualization and visual analytics
visual analytics
0.112009
Vispedia: on-demand data integration for interactive visualization and exploration · SIGMOD Conference 2009
Visualization and visual analytics
data visualization
0.112008
Vispedia: Interactive Visual Exploration of Wikipedia Data via Search-Based Integration · IEEE Trans. Vis. Comput. Graph. 2008
Visualization and visual analytics › information visualization
heterogeneous data visualization
0.112007
Visualization of Heterogeneous Data · IEEE Trans. Vis. Comput. Graph. 2007
Rendering
appearance modeling
0.012003
Light scattering from human hair fibers · ACM Trans. Graph. 2003
Rendering › reflectance modeling
fiber scattering
0.012003
Light scattering from human hair fibers · ACM Trans. Graph. 2003
Rendering
real-time rendering
0.012003
Shadow silhouette maps · ACM Trans. Graph. 2003
Rendering › shading
shading models
0.012003
Light scattering from human hair fibers · ACM Trans. Graph. 2003
Rendering › shadow rendering
shadow mapping
0.012003
Shadow silhouette maps · ACM Trans. Graph. 2003
Rendering
shadow rendering
0.012003
Shadow silhouette maps · ACM Trans. Graph. 2003
Data models and query languages › semistructured data
RDF data
0.012007
Visualization of Heterogeneous Data · IEEE Trans. Vis. Comput. Graph. 2007

Methods — techniques the papers use, named apart from their topics

keyword query · 0.2graph search · 0.2search-based integration · 0.2path search · 0.2schema matching · 0.1measurement-based shading model · 0.0analytical cylinder scattering · 0.0
YearPublicationVenuePosition
2009 Vispedia: on-demand data integration for interactive visualization and exploration
abstract
Wikipedia is an example of the large, collaborative, semi-structured data sets emerging on the Web. Typically, before these data sets can be used, they must transformed into structured tables via data integration. We present Vispedia, a Web-based visualization system which incorporates data integration into an iterative, interactive data exploration and analysis process. This reduces the upfront cost of using heterogeneous data sets like Wikipedia. Vispedia is driven by a keyword-query-based integration interface implemented using a fast graph search. The search occurs interactively over DBpedia's semantic graph of Wikipedia, without depending on the existence of a structured ontology. This combination of data integration and visualization enables a broad class of non-expert users to more effectively use the semi-structured data available on the Web.
Bryan Chan 0001, Justin Talbot, Leslie Wu, Nathan Sakunkoo, Mike Cammarano, Pat Hanrahan
SIGMOD Conference5
2008 Vispedia: Interactive Visual Exploration of Wikipedia Data via Search-Based Integration
abstract
Wikipedia is an example of the collaborative, semi-structured data sets emerging on the Web. These data sets have large, non-uniform schema that require costly data integration into structured tables before visualization can begin. We present Vispedia, a Web-based visualization system that reduces the cost of this data integration. Users can browse Wikipedia, select an interesting data table, then use a search interface to discover, integrate, and visualize additional columns of data drawn from multiple Wikipedia articles. This interaction is supported by a fast path search algorithm over DBpedia, a semantic graph extracted from Wikipedia's hyperlink structure. Vispedia can also export the augmented data tables produced for use in traditional visualization systems. We believe that these techniques begin to address the "long tail" of visualization by allowing a wider audience to visualize a broader class of data. We evaluated this system in a first-use formative lab study. Study participants were able to quickly create effective visualizations for a diverse set of domains, performing data integration as needed.
Bryan Chan 0001, Leslie Wu, Justin Talbot, Mike Cammarano, Pat Hanrahan
IEEE Trans. Vis. Comput. Graph.4
2007 Visualization of Heterogeneous Data
abstract
Both the Resource Description Framework (RDF), used in the semantic web, and Maya Viz u-forms represent data as a graph of objects connected by labeled edges. Existing systems for flexible visualization of this kind of data require manual specification of the possible visualization roles for each data attribute. When the schema is large and unfamiliar, this requirement inhibits exploratory visualization by requiring a costly up-front data integration step. To eliminate this step, we propose an automatic technique for mapping data attributes to visualization attributes. We formulate this as a schema matching problem, finding appropriate paths in the data model for each required visualization attribute in a visualization template.
Mike Cammarano, Xin Dong 0001, Bryan Chan 0001, Jeff Klingner, Justin Talbot, Alon Y. Halevy, Pat Hanrahan
IEEE Trans. Vis. Comput. Graph.1
2003 Light scattering from human hair fibers
abstract
Light scattering from hair is normally simulated in computer graphics using Kajiya and Kay's classic phenomenological model. We have made new measurements of scattering from individual hair fibers that exhibit visually significant effects not predicted by Kajiya and Kay's model. Our measurements go beyond previous hair measurements by examining out-of-plane scattering, and together with this previous work they show a multiple specular highlight and variation in scattering with rotation about the fiber axis. We explain the sources of these effects using a model of a hair fiber as a transparent elliptical cylinder with an absorbing interior and a surface covered with tilted scales. Based on an analytical scattering function for a circular cylinder, we propose a practical shading model for hair that qualitatively matches the scattering behavior shown in the measurements. In a comparison between a photograph and rendered images, we demonstrate the new model's ability to match the appearance of real hair.
Steve Marschner, Henrik Wann Jensen, Mike Cammarano, Steve Worley, Pat Hanrahan
ACM Trans. Graph.3
2003 Shadow silhouette maps
abstract
The most popular techniques for interactive rendering of hard shadows areshadow mapsandshadow volumes. Shadow maps work well in regions that are completely in light or in shadow but result in objectionable artifacts near shadow boundaries. In contrast, shadow volumes generate precise shadow boundaries but require high fill rates. In this paper, we propose the method ofsilhouette maps, in which a shadow depth map is augmented by storing the location of points on the geometric silhouette. This allows the shader to construct a piecewise linear approximation to the true shadow silhouette, improving the visual quality over the piecewise constant approximation of conventional shadow maps. We demonstrate an implementation of our approach running on programmable graphics hardware in real-time.
Pradeep Sen, Mike Cammarano, Pat Hanrahan
ACM Trans. Graph.2