Focus+context grouping for animated transitions. (October 2018)

• Record Type: Journal Article
• Authors: Zheng, Yixian; Wu, Wenchao; Cao, Nan; Qu, Huamin; Ni, Lionel M.
• Is Part Of: Journal of visual languages & computing. Volume 48(2018)
• Page Start: 61
• Page End: 69
• Publication Date: 2018-10
• Subjects: Animated transitions -- Grouping -- Visual tracking -- Visualization; Visual programming languages (Computer science) -- Periodicals; Visual programming (Computer science) -- Periodicals; Programming languages (Electronic computers) -- Semantics -- Periodicals; Langages de programmation visuelle -- Périodiques; Programmation visuelle -- Périodiques; Langages de programmation -- Sémantique -- Périodiques; Programming languages (Electronic computers) -- Semantics; Visual programming (Computer science); Visual programming languages (Computer science); Periodicals; Electronic journals; 005
• DOI: 10.1016/j.jvlc.2018.06.006
• Languages: English
• ISSNs: 1045-926X

Abstract

Abstract: Animation is a commonly used technique in information visualization for smooth transitions between different views. When observing animations of moving objects, people often need to track several specific objects while identify the major trend of movement simultaneously. In this paper, we propose a novel focus+context grouping technique to facilitate target tracking and trend identification. It divides objects into several groups based on a comprehensive tree cut algorithm and generates a staggering animation in which groups are animated sequentially. A balance between efficiency and accuracy is achieved for an effective animation planning. To evaluate the effectiveness of the proposed technique, a carefully designed user study is conducted. The results indicate that focus+context grouping is effective for users to track targets without losing context (i.e., major trend of movement). Based on the study, we discuss advantages and limitations of the proposed grouping technique and conclude with design implications.