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Martin Field

dblp:34/9592 · DBLP profile ↗
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3ranked-venue papers
2as first author
0since 2021 · last 2011
—ORCID · none

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

Graphics, computer vision, multimedia, augmented reality and games · 2 · 2 first-authorArtificial intelligence and machine learning · 1 · 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.

Human-computer interaction and pervasive computing
1 paper
Interaction techniques and input · 100%
Computer graphics and multimedia
1 paper
Geometric modeling and processing · 100%

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

TopicWeightPapersLastEvidence papers
Interaction techniques and input › sketch-based interaction
sketch recognition
0.112011
Sketch Recognition Algorithms for Comparing Complex and Unpredictable Shapes · IJCAI 2011
Geometric modeling and processing › shape analysis
shape comparison
0.012011
Sketch Recognition Algorithms for Comparing Complex and Unpredictable Shapes · IJCAI 2011

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

sketch recognition · 0.2
YearPublicationVenuePosition
2011 Evaluation of a natural sketch interface for truss FBDs and analysis
abstract
Mechanix is a sketch recognition tool that provides an efficient means for engineering students to learn how to draw truss free-body diagrams (FBDs) and solve truss problems. The system allows students to sketch these FBDs into a tablet computer or by using a mouse just as they would by hand, a mouse can also be used to draw the sketch using a regular computer and monitor. Mechanix is then able to provide immediate feedback to the students and tell them if they are missing any components of the FBD, without providing answers. The program is also able to tell them whether their solved reaction or member forces are correct or not. This paper presents a study to evaluate the effectiveness and advantages of using Mechanix in the classroom, as a supplement to traditional teaching and learning methods. Current results demonstrate that students believe Mechanix enhances their learning and are highly engaged when using it. Future work on the refinement of the program is also discussed.
Olufunmilola Atilola, Martin Field, Erin McTigue, Tracy Anne Hammond, Julie Linsey
FIE2
2011 Sketch Recognition Algorithms for Comparing Complex and Unpredictable Shapes
abstract
In an introductory Engineering course with an annual enrollment of over 1000 students, a professor has little option but to rely on multiple choice exams for midterms and finals. Furthermore, the teaching assistants are too overloaded to give detailed feedback on submitted homework assignments. We introduce Mechanix, a computer-assisted tutoring system for engineering students. Mechanix uses recognition of freehand sketches to provide instant, detailed, and formative feedback as the student progresses through each homework assignment, quiz, or exam. Free sketch recognition techniques allow students to solve free-body diagram and static truss problems as if they were using a pen and paper. The same recognition algorithms enable professors to add new unique problems simply by sketching out the correct answer. Mechanix is able to ease the burden of grading so that instructors can assign more free response questions, which provide a better measure of student progress than multiple choice questions do.
Martin Field, Stephanie Valentine, Julie Linsey, Tracy Anne Hammond
IJCAI1
2010 The effect of task on classification accuracy: Using gesture recognition techniques in free-sketch recognition
Martin Field, Sam Gordon, Eric Jeffrey Peterson, Raquel Robinson, Thomas F. Stahovich, Christine Alvarado
Comput. Graph.1