Sarkis Halladjian

dblp:245/8926 · DBLP profile ↗
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3ranked-venue papers
2as first author
2since 2021 · last 2023
—ORCID · none

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

Graphics, computer vision, multimedia, augmented reality and games · 3 · 2 first-author · 2 since 2021

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
3 papers
Visualization and visual analytics · 100%
Interdisciplinary, comprehensive, and emerging computing
2 papers
Bioinformatics and computational biology · 100%

Topics — the 7 heaviest of 7, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Visualization and visual analytics › biological data visualization
genomic data visualization
1.022022
Multiscale Unfolding: Illustratively Visualizing the Whole Genome at a Glance · IEEE Trans. Vis. Comput. Graph. 2022
Scale Trotter: Illustrative Visual Travels Across Negative Scales · IEEE Trans. Vis. Comput. Graph. 2020
Visualization and visual analytics › scientific visualization
illustrative visualization
1.022022
Multiscale Unfolding: Illustratively Visualizing the Whole Genome at a Glance · IEEE Trans. Vis. Comput. Graph. 2022
Scale Trotter: Illustrative Visual Travels Across Negative Scales · IEEE Trans. Vis. Comput. Graph. 2020
Visualization and visual analytics › scientific visualization
multiscale visualization
1.022022
Multiscale Unfolding: Illustratively Visualizing the Whole Genome at a Glance · IEEE Trans. Vis. Comput. Graph. 2022
Scale Trotter: Illustrative Visual Travels Across Negative Scales · IEEE Trans. Vis. Comput. Graph. 2020
Visualization and visual analytics › scientific visualization
molecular visualization
0.712023
Molecumentary: Adaptable Narrated Documentaries Using Molecular Visualization · IEEE Trans. Vis. Comput. Graph. 2023
Visualization and visual analytics › data storytelling
narrative visualization
0.712023
Molecumentary: Adaptable Narrated Documentaries Using Molecular Visualization · IEEE Trans. Vis. Comput. Graph. 2023
Visualization and visual analytics
scientific visualization
0.712023
Molecumentary: Adaptable Narrated Documentaries Using Molecular Visualization · IEEE Trans. Vis. Comput. Graph. 2023
Bioinformatics and computational biology
genomics
0.322022
Multiscale Unfolding: Illustratively Visualizing the Whole Genome at a Glance · IEEE Trans. Vis. Comput. Graph. 2022
Scale Trotter: Illustrative Visual Travels Across Negative Scales · IEEE Trans. Vis. Comput. Graph. 2020

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

transparency interpolation · 1.1level unfolding · 1.1illustrative visualization · 1.1scale-dependent camera model · 0.92d/3d integrated rendering · 0.9text-to-speech · 0.7story graph · 0.7automated camera transitions · 0.7
YearPublicationVenuePosition
2023 Molecumentary: Adaptable Narrated Documentaries Using Molecular Visualization
abstract
We present a method for producing documentary-style content using real-time scientific visualization. We introduce molecumentaries, i.e., molecular documentaries featuring structural models from molecular biology, created through adaptable methods instead of the rigid traditional production pipeline. Our work is motivated by the rapid evolution of scientific visualization and it potential in science dissemination. Without some form of explanation or guidance, however, novices and lay-persons often find it difficult to gain insights from the visualization itself. We integrate such knowledge using the verbal channel and provide it along an engaging visual presentation. To realize the synthesis of a molecumentary, we provide technical solutions along two major production steps: (1) preparing a story structure and (2) turning the story into a concrete narrative. In the first step, we compile information about the model from heterogeneous sources into a story graph. We combine local knowledge with external sources to complete the story graph and enrich the final result. In the second step, we synthesize a narrative, i.e., story elements presented in sequence, using the story graph. We then traverse the story graph and generate a virtual tour, using automated camera and visualization transitions. We turn texts written by domain experts into verbal representations using text-to-speech functionality and provide them as a commentary. Using the described framework, we synthesize fly-throughs with descriptions: automatic ones that mimic a manually authored documentary or semi-automatic ones which guide the documentary narrative solely through curated textual input.
David Kouril, Ondrej Strnad, Peter Mindek, Sarkis Halladjian, Tobias Isenberg 0001, M. Eduard Gröller, Ivan Viola
IEEE Trans. Vis. Comput. Graph.4
2022 Multiscale Unfolding: Illustratively Visualizing the Whole Genome at a Glance
abstract
We present Multiscale Unfolding, an interactive technique for illustratively visualizing multiple hierarchical scales of DNA in a single view, showing the genome at different scales and demonstrating how one scale spatially folds into the next. The DNA's extremely long sequential structure-arranged differently on several distinct scale levels-is often lost in traditional 3D depictions, mainly due to its multiple levels of dense spatial packing and the resulting occlusion. Furthermore, interactive exploration of this complex structure is cumbersome, requiring visibility management like cut-aways. In contrast to existing temporally controlled multiscale data exploration, we allow viewers to always see and interact with any of the involved scales. For this purpose we separate the depiction into constant-scale and scale transition zones. Constant-scale zones maintain a single-scale representation, while still linearly unfolding the DNA. Inspired by illustration, scale transition zones connect adjacent constant-scale zones via level unfolding, scaling, and transparency. We thus represent the spatial structure of the whole DNA macro-molecule, maintain its local organizational characteristics, linearize its higher-level organization, and use spatially controlled, understandable interpolation between neighboring scales. We also contribute interaction techniques that provide viewers with a coarse-to-fine control for navigating within our all-scales-in-one-view representations and visual aids to illustrate the size differences. Overall, Multiscale Unfolding allows viewers to grasp the DNA's structural composition from chromosomes to the atoms, with increasing levels of "unfoldedness," and can be applied in data-driven illustration and communication.
Sarkis Halladjian, David Kouril, Haichao Miao, M. Eduard Gröller, Ivan Viola, Tobias Isenberg 0001
IEEE Trans. Vis. Comput. Graph.1
2020 Scale Trotter: Illustrative Visual Travels Across Negative Scales
abstract
We present ScaleTrotter, a conceptual framework for an interactive, multi-scale visualization of biological mesoscale data and, specifically, genome data. ScaleTrotter allows viewers to smoothly transition from the nucleus of a cell to the atomistic composition of the DNA, while bridging several orders of magnitude in scale. The challenges in creating an interactive visualization of genome data are fundamentally different in several ways from those in other domains like astronomy that require a multi-scale representation as well. First, genome data has intertwined scale levels-the DNA is an extremely long, connected molecule that manifests itself at all scale levels. Second, elements of the DNA do not disappear as one zooms out-instead the scale levels at which they are observed group these elements differently. Third, we have detailed information and thus geometry for the entire dataset and for all scale levels, posing a challenge for interactive visual exploration. Finally, the conceptual scale levels for genome data are close in scale space, requiring us to find ways to visually embed a smaller scale into a coarser one. We address these challenges by creating a new multi-scale visualization concept. We use a scale-dependent camera model that controls the visual embedding of the scales into their respective parents, the rendering of a subset of the scale hierarchy, and the location, size, and scope of the view. In traversing the scales, ScaleTrotter is roaming between 2D and 3D visual representations that are depicted in integrated visuals. We discuss, specifically, how this form of multi-scale visualization follows from the specific characteristics of the genome data and describe its implementation. Finally, we discuss the implications of our work to the general illustrative depiction of multi-scale data.
Sarkis Halladjian, Haichao Miao, David Kouril, M. Eduard Gröller, Ivan Viola, Tobias Isenberg 0001
IEEE Trans. Vis. Comput. Graph.1