Creative Segment: A descriptive theory applied to computer-aided sketching

Sun, Lingyun; Wei, Xiang; Chai, Chunlei; Wang, Changlu; Huang, Qiangsheng

doi:10.1016/j.destud.2013.10.003

Cited by 32 publications

(27 citation statements)

References 35 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The fact that brain, hand and eye actions are tightly connected in the sketching process [55,56,5] suggests that bioelectric interfaces potentially extract normal sketching patterns directly from forearm EMG signals. Analogously, the SVM classifier was able to recognize seven one-stroke shapes with nearly perfect accuracy.…”

Section: Discussionmentioning

confidence: 99%

“…Thus, the analysis and estimation of sketching in this area is very significant. More natural sketching recognition is helpful for the development of electronic sketching systems [1], computer aided sketching systems [5] and sketch-based interfaces for modeling in Computer-Aided Design (CAD) systems [6]. Despite substantial progress in this area, recognizing sketching remains a difficult problem due to the fact that sketches are informal, ambiguous and implicit [7].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Recognition of sketching from surface electromyography

Chen

Zhong

Gong

et al. 2017

Neural Comput & Applic

View full text Add to dashboard Cite

The main objective of this study is to recognize sketching precisely and effectively in human computer interaction. A surface electromyography (sEMG) based sketching recognition method is proposed. We conducted an experiment in which we recorded the sEMG signals from the forearm muscles of two participants who were instructed to sketch seven basic one-stroke shapes. Subsequently, seven features of the sEMG time domain were extracted. After reducing data dimensionality using principal component analysis, these features were used as input vectors to a sketching recognition model based on Support Vector Machines (SVM). The performance of this model was compared to two other recognition models based on Multilayer perceptron (MLP) neural networks and Self Organization Feature Map (SOFM) neural networks. The average recognition rates for the seven basic one-stroke shapes of two participants achieved by the SVM-based and MLP-based models were both 98.5% in the test set, which were slightly superior to the performance of the SOFM classifier. Our results demonstrate the feasibility of converting forearm sEMG signals into sketching patterns.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Recognition of sketching from surface electromyography

Chen

Zhong

Gong

et al. 2017

Neural Comput & Applic

View full text Add to dashboard Cite

show abstract

“…is a common way to do that (Sun et al 2014;Suwa and Tversky 1997). As previous research has shown, sketching enables a focus shift in design processes (Sun et al 2014;Suwa and Tversky 1997). With transition we focus on another aspect of this focus shift, as seen in the two pairs we examined.…”

Section: Transition Of Perspectivementioning

confidence: 99%

“…This happens not only through talk, but also by using sketches, gestures, enactments or drama (Arvola and Artman 2007;Juhl and Lindegaard 2013;Ramberg et al 2013;Sun et al 2014;Suwa and Tversky 1997;Tholander et al 2008). For example Juhl and Lindegaard (2013), in their studies of engineering students solving design tasks, conclude that sketching helped the students synthesize ideas, and facilitated mutual understanding and decision-making.…”

Section: Common Groundmentioning

confidence: 99%

See 1 more Smart Citation

A model to analyse students’ cooperative idea generation in conceptual design

Hultén

Artman

House

2016

Int J Technol Des Educ

View full text Add to dashboard Cite

In this article we focus on the co-creation of ideas. Through the use of concepts from collaborative learning and communication theory we suggest a model that will enable the cooperative nature of creative design tasks to emerge. Four objectives of the model are stated and elaborated on in the paper: that the model should be anchored in previous research; that it should allow for collaborative aspects of creative design to be accounted for; that it should address the mechanisms by which new ideas are generated, embraced and cultivated during actual design; and that it should have a firm theoretical grounding. The model is also exemplified by two test sessions where two student pairs perform a timeconstrained design task. We hope that the model can play a role both as an educational tool to be used by students and a teacher in design education, but primarily as a model to analyse students' cooperative idea generation in conceptual design.

show abstract

Development of More Concept Words Leads to the Generation of More Idea Sketches

Cheng

2021

Lecture Notes in Computer Science

View full text Add to dashboard Cite

Creative Segment: A descriptive theory applied to computer-aided sketching

Cited by 32 publications

References 35 publications

Recognition of sketching from surface electromyography

Recognition of sketching from surface electromyography

A model to analyse students’ cooperative idea generation in conceptual design

Development of More Concept Words Leads to the Generation of More Idea Sketches

Contact Info

Product

Resources

About