Crowdsourcing Facial Expressions Using Popular Gameplay

BeFaced is a facial expression tablet game that enables massive crowdsourcing of targeted facial expressions to build a large high quality dataset for the advancement of affective computing. BeFaced uses the psychological draw of popular tile-matching gameplay coupled with a dynamic facial expression recognition engine to balance gameplay.

Chek Tien Tan, University of Technology, Sydney
Daniel Rosser, University of Technology, Sydney
Natalie Harrold, University of Technology, Sydney

Interactive Art “The Qi of Calligraphy”: Dance and Imprint

In Chinese calligraphy, the concept of “promoting the circulation of qi” enables Chinese characters to express the essence, qi, and spirit of the calligrapher through the proper use of force and speed. As a result, the emotions and soul of the calligrapher are recorded in a work of Chinese calligraphy.

Helin Luo, National Taiwan University

A Study on the Degrees of Freedom in Touchless Interaction

Touchless interfaces have not yet been tailored to interact with 3D data, since it requires at least three DOF. We present a user study in which a mouse-based interface has been compared with two Kinect-based touchless interfaces that allow users to interact with up to nine DOF

Luigi Gallo, National Research Council of Italy

Data-driven Suggestions for Portrait Posing

With the help of a consumer-level depth sensor, our technique automatically produces data-driven posing suggestions, which can serve as either visual guidance or stimulate creativity for portrait photographers. Our tool greatly helps unskilled photographers create aesthetically pleasing portraits with diversity.

Hongbo Fu, City University of Hong Kong
Xiaoguang Han, City University of Hong Kong
Quoc Huy Phan, City University of Hong Kong