Sujin Jang, Niklas Elmqvist, Karthik Ramani
GestureAnalyzer: Visual Analytics for Pattern Analysis of Mid-Air Hand Gestures
Proceedings of the ACM Symposium on Spatial User Interaction, October 4-5, 2014, Honolulu, HI, USA

Understanding the intent behind human gestures is a critical  problem in the design of gestural interactions. A common method to observe and understand how users express gestures is to use elicitation studies. However, these studies requires time-consuming analysis of user data to identify gesture patterns. Also, the analysis by humans cannot describe gestures in as detail as in data-based representations of motion features. In this paper, we present GestureAnalyzer, a system that supports exploratory analysis of gesture patterns by applying interactive clustering and visualization techniques to motion tracking data. GestureAnalyzer enables rapid categorization of similar gestures, and visual investigation of various geometric and kinematic properties of user gestures. We describe the system components, and then demonstrate its utility through a case study on mid-air hand gestures obtained from elicitation studies.


The GestureAnalyzer interface. (A) is a list of tasks loaded from the database. (B) shows a table of user IDs. (C) shows the animation of user gestures. (D) is a panel that shows the interactive hierarchical clustering of gesture data. Information of currently selected task and cluster node are given at the bottom. (E) is a list of output clusters generated from the interactive hierarchical clustering. (F) provides a visual definition of gesture feature. (G) shows a tree diagram of gesture clusters.

About Sujin Jang

Sujin Jang received his Ph.D. in August 2017 from the School of Mechanical Engineering at Purdue University. His research work in the C-Design Lab broadly involved human-computer interaction, visual analytics, and machine learning. In particular, the goal of his research aimed (i) to create natural human-computer interaction systems using the human body as an interaction input and (ii) to establish the fundamental principles when designing such novel interaction systems. His past research experience also includes computer vision, robotics, and non-linear control/estimation. He has received the Estus H. and Vashti L. Magoon Award for Teaching Excellence in 2015.  Currently, he is a staff research member at the Motorola-Lenovo Research group. [Personal Website][LinkedIn]

Tagged with:
Posted in 2014, HUMAN SHAPE INTERACTION, Karthik Ramani, Mid-air Interaction, Spatial Analytics, Sujin Jang