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Andrew M. Lovett

dblp:60/5729 · DBLP profile ↗
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14ranked-venue papers
8as first author
4since 2021 · last 2025
0009-0007-4463-1946ORCID · reported

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

Artificial intelligence and machine learning · 13 · 8 first-author · 3 since 2021Applied, interdisciplinary, general and emerging computing · 11 · 7 first-author · 3 since 2021Graphics, computer vision, multimedia, augmented reality and games · 3 · 1 first-author · 1 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
1 paper
Visualization and visual analytics · 100%
Artificial intelligence
2 papers
Knowledge representation and reasoning · 35% Vision and language · 35% Image recognition and object detection · 30%

Topics — the 8 heaviest of 8, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Visualization and visual analytics
graphical perception
0.812024
What Does the Chart Say? Grouping Cues Guide Viewer Comparisons and Conclusions in Bar Charts · IEEE Trans. Vis. Comput. Graph. 2024
Visualization and visual analytics › perception
perception in visualization
0.812024
What Does the Chart Say? Grouping Cues Guide Viewer Comparisons and Conclusions in Bar Charts · IEEE Trans. Vis. Comput. Graph. 2024
Visualization and visual analytics
visual comparison
0.812024
What Does the Chart Say? Grouping Cues Guide Viewer Comparisons and Conclusions in Bar Charts · IEEE Trans. Vis. Comput. Graph. 2024
Visualization and visual analytics › visual encoding
bar chart
0.212024
What Does the Chart Say? Grouping Cues Guide Viewer Comparisons and Conclusions in Bar Charts · IEEE Trans. Vis. Comput. Graph. 2024
Knowledge, reasoning and agents › Knowledge representation and reasoning
qualitative reasoning
0.112008
CogSketch · AAAI 2008
Computer vision › Vision and language
sketch understanding
0.112008
CogSketch · AAAI 2008
Computer vision › Image recognition and object detection › object recognition › shape-based object recognition
sketch recognition
0.112007
Incremental Learning of Perceptual Categories for Open-Domain Sketch Recognition · IJCAI 2007
Learning and educational technologies › multimedia learning
sketch-based learning
0.012008
CogSketch · AAAI 2008

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

crowdsourced experiment · 0.8
YearPublicationVenuePosition
2025 Visualizing Motion Traces Enhances Pursuit Detection in Dynamic Scenes
Yishu Ji, Maria Kon, Andrew M. Lovett, Mark Livingston, Sangeet S. Khemlani, Yalong Yang 0001, Cindy Xiong Bearfield
CogSci3
2024 Measuring and Modeling Pursuit Detection in Dynamic Visual Scenes
Maria Kon, Sangeet S. Khemlani, Andrew M. Lovett
CogSci3
2024 What Does the Chart Say? Grouping Cues Guide Viewer Comparisons and Conclusions in Bar Charts
abstract
Reading a visualization is like reading a paragraph. Each sentence is a comparison: the mean of these is higher than those; this difference is smaller than that. What determines which comparisons are made first? The viewer's goals and expertise matter, but the way that values are visually grouped together within the chart also impacts those comparisons. Research from psychology suggests that comparisons involve multiple steps. First, the viewer divides the visualization into a set of units. This might include a single bar or a grouped set of bars. Then the viewer selects and compares two of these units, perhaps noting that one pair of bars is longer than another. Viewers might take an additional third step and perform a second-order comparison, perhaps determining that the difference between one pair of bars is greater than the difference between another pair. We create a visual comparison taxonomy that allows us to develop and test a sequence of hypotheses about which comparisons people are more likely to make when reading a visualization. We find that people tend to compare two groups before comparing two individual bars and that second-order comparisons are rare. Visual cues like spatial proximity and color can influence which elements are grouped together and selected for comparison, with spatial proximity being a stronger grouping cue. Interestingly, once the viewer grouped together and compared a set of bars, regardless of whether the group is formed by spatial proximity or color similarity, they no longer consider other possible groupings in their comparisons.
Cindy Xiong Bearfield, Chase Stokes, Andrew M. Lovett, Steven Franconeri
IEEE Trans. Vis. Comput. Graph.3
2021 Selection, Engagement, & Enhancement: A Framework for Modeling Visual Attention
Andrew M. Lovett, Will Bridewell, Paul Bello
CogSci1
2019 Attentional Capture: Modeling Automatic Mechanisms and Top-Down Control
Andrew M. Lovett, Will Bridewell, Paul Bello
CogSci1
2018 An Attention-Driven Computational Model of Human Causal Reasoning
Paul Bello, Andrew M. Lovett, Gordon Briggs, Kevin O'Neill
CogSci2
2017 Goal-Directed Deployment of Attention in a Computational Model: A Study in Multiple-Object Tracking
Andrew M. Lovett, Will Bridewell, Paul Bello
CogSci1
2015 Topological Relations between Objects Are Categorically Coded
Andrew M. Lovett, Steven Franconeri
CogSci1
2014 Modeling Spatial Abstraction during Mental Rotation
Andrew M. Lovett, Holger Schultheis
CogSci1
2013 Glushko Dissertation Prize Symposium
Douglas Knox Bemis, Neil Cohn, George Kachergis, Andrew M. Lovett, Robert L. Goldstone
CogSci4
2013 Modeling Spatial Ability in Mental Rotation and Paper-Folding
Andrew M. Lovett, Kenneth D. Forbus
CogSci1
2012 Modeling Multiple Strategies for Solving Geometric Analogy Problems
Andrew M. Lovett, Kenneth D. Forbus
CogSci1
2008 CogSketch
Kenneth D. Forbus, Andrew M. Lovett, Kate Lockwood, Jon Wetzel, Camillia Matuk, Benjamin D. Jee, Jeffrey M. Usher
AAAI2
2007 Incremental Learning of Perceptual Categories for Open-Domain Sketch Recognition
Andrew M. Lovett, Morteza Dehghani, Kenneth D. Forbus
IJCAI1