GRAPHICLAND

Data-Driven Suggestions For Portrait Posing

This work introduces an easy-to-use creativity support tool for portrait posing, which is an important but challenging problem in portrait photography. While it is well known that a collection of sample poses is a source of inspiration, manual browsing is the only option to identify a desired pose from a possibly large collection of poses. With our tool, a photographer is able to easily retrieve desired reference poses as guidance or stimulate creativity. We show how our data-driven suggestions can be effectively used to either refine the current pose of a subject or explore new poses. Our tool greatly helps unskilled photographers create aesthetically pleasing portraits with diversity. Our work takes the first step of using consumer-level depth sensors towards more intelligent cameras for computational photography.

http://sa2013.siggraph.org/en/attendees/emerging-technologies.html?view=event&type=etech&event=72