Learning from facial aging patterns for automatic age estimation

Age Specific Human-Computer Interaction (ASHCI) has vast potential applications in daily life. However, automatic age estimation technique is still underdeveloped. One of the main reasons is that the aging effects on human faces present several unique characteristics which make age estimation a challenging task that requires non-standard classification approaches. According to the speciality of the facial aging effects, this paper proposes the AGES (AGing pattErn Sub-space) method for automatic age estimation. The basic idea is to model the aging pattern, which is defined as a sequence of personal aging face images, by learning a representative subspace. The proper aging pattern for an unseen face image is then determined by the projection in the subspace that can best reconstruct the face image, while the position of the face image in that aging pattern will indicate its age. The AGES method has shown encouraging performance in the comparative experiments either as an age estimator or as an age range estimator.

Synchronous Objects for One Flat Thing, reproduced

Synchronous Objects is a website where a visitor/ reader can investigate the interlocking systems of organisation in the choreography of William Forsythe's dance One Flat Thing, reproduced (2000). These systems were quantified through the collection of data and transformed into a series of objects - synchronous objects - that work in harmony to explore these choreographic structures, reveal their patterns and re-imagine what they might look like. The goal of the project was to create a learning platform to engage a broad public in this exploration of choreography, to explore cross-disciplinary research and to stimulate creative discovery for specialists and non-specialists alike.

A risk worth taking: perceived risk as moderator of satisfaction, loyalty, and willingness-to-pay premium price

This research investigates the moderating role of perceived risk in the relationship between satisfaction, loyalty, and willingness to pay premium price (WTP). A total of 364 respondents were recruited from Amazon's Mechanical Turk panel. Financial, social, performance, and psychological risks have significant negative effects on the relationship between satisfaction and WTP, whereas only financial risks have significant negative effects on the relationship between loyalty and WTP. Using moderated mediation analysis, we found that the mediating effects of loyalty diminish significantly in high social risk conditions and diminish completely in high financial risk conditions.