Cem Memili

dblp:167/3298 · DBLP profile ↗
← Back
2ranked-venue papers
0as first author
0since 2021 · last 2016
—ORCID · none

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

Graphics, computer vision, multimedia, augmented reality and games · 2Human-computer interaction and ubiquitous computing · 2

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
1 paper
Visualization and visual analytics · 77% Rendering · 23%

Topics — the 1 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Visualization and visual analytics › information visualization
attention visualization
0.212015
GPU-accelerated attention map generation for dynamic 3D scenes · VR 2015

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

GPU acceleration · 0.2
YearPublicationVenuePosition
2016 Model-based real-time visualization of realistic three-dimensional heat maps for mobile eye tracking and eye tracking in virtual reality
abstract
Heat maps, or more generally, attention maps or saliency maps are an often used technique to visualize eye-tracking data. With heat maps qualitative information about visual processing can be easily visualized and communicated between experts and laymen. They are thus a versatile tool for many disciplines, in particular for usability engineering, and are often used to get a first overview about recorded eye-tracking data.
Thies Pfeiffer, Cem Memili
ETRA2
2015 GPU-accelerated attention map generation for dynamic 3D scenes
abstract
Measuring visual attention has become an important tool during product development. Attention maps are important qualitative visualizations to communicate results within the team and to stakeholders. We have developed a GPU-accelerated approach which allows for real-time generation of attention maps for 3D models that can, e.g., be used for on-the-fly visualizations of visual attention distributions and for the generation of heat-map textures for offline high-quality renderings. The presented approach is unique in that it works with monocular and binocular data, respects the depth of focus, can handle moving objects and is ready to be used for selective rendering.
Thies Pfeiffer, Cem Memili
VR2