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Christian Santoni

dblp:166/3685 · DBLP profile ↗
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4ranked-venue papers
1as first author
0since 2021 · last 2019
0000-0001-8083-8310ORCID · corroborated

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

Graphics, computer vision, multimedia, augmented reality and games · 4 · 1 first-authorHuman-computer interaction and ubiquitous computing · 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
2 papers
Geometric modeling and processing · 68% Visual content generation and editing · 32%

Topics — the 3 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Geometric modeling and processing › procedural modeling
shape grammar
0.212016
gTangle: a grammar for the procedural generation of tangle patterns · ACM Trans. Graph. 2016
Geometric modeling and processing › shape modeling › shape editing
mesh editing
0.212015
MeshHisto: collaborative modeling by sharing and retargeting editing histories · ACM Trans. Graph. 2015
Geometric modeling and processing › computational geometry
polygon decomposition
0.112016
gTangle: a grammar for the procedural generation of tangle patterns · ACM Trans. Graph. 2016

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

set grammar · 0.2group grammar · 0.2mesh difference encoding · 0.2distributed version control · 0.2conflict detection · 0.2
YearPublicationVenuePosition
2019 Grammar-based procedural animations for motion graphics
Edoardo Carra, Christian Santoni, Fabio Pellacini
Comput. Graph.2
2018 gMotion: A Spatio-Temporal Grammar for the Procedural Generation of Motion Graphics
Edoardo Carra, Christian Santoni, Fabio Pellacini
Graphics Interface2
2016 gTangle: a grammar for the procedural generation of tangle patterns
abstract
Tangles are a form of structured pen-and-ink 2D art characterized by repeating, recursive patterns. We present a method to procedurally generate tangle drawings, seen as recursively split sets of arbitrary 2D polygons with holes, with anisotropic and non-stationary features. We formally model tangles with group grammars, an extension of set grammars, that explicitly handles the grouping of shapes necessary to represent tangle repetitions. We introduce a small set of expressive geometric and grouping operators, showing that they can respectively express complex tangles patterns and sub-pattern distributions, with relatively simple grammars. We also show how users can control tangle generation in an interactive and intuitive way. Throughout the paper, we show how group grammars can, in few tens of seconds, produce a wide variety of patterns that would take artists hours of tedious and time-consuming work. We then validated both the quality of the generated tangles and the efficiency of the control provided to the users with a user study, run with both expert and non-expert users.
Christian Santoni, Fabio Pellacini
ACM Trans. Graph.1
2015 MeshHisto: collaborative modeling by sharing and retargeting editing histories
abstract
Current modeling packages have polished interfaces for editing polygonal meshes, where artists work individually on each mesh. A variety of recent cloud-based services have shown the benefits of editing documents in real-time collaboration with others. In this paper, we present a system for collaborative editing of low-polygonal and subdivision mesh models. We cast collaborative editing as a special instance of distributed version control. We support concurrent editing by robustly sharing and merging mesh version histories in real-time. We store and transmit mesh differences efficiently by encoding them as sequences of primitive editing operations. We enable collaboration by merging and detecting conflicts. We extend this model letting artists adapt others' editing histories by retargeting sequences of editing operations to new parts of the mesh with potentially different topology. We tested our algorithms by editing meshes with up to thousand edits, in collaborative editing sessions lasting a few hours, and by retargeting sequences of several hundred edits. We found the proposed system to be reliable, fast and scaling well with mesh complexity. We demonstrate that our merge algorithm is more robust than prior work. We further validated the proposed collaborative workflow with a user study where MeshHisto was consistently preferred over other alternatives for collaborative workflows.
Gabriele Salvati, Christian Santoni, Valentina Tibaldo, Fabio Pellacini
ACM Trans. Graph.2