Peter O. Stubler

Dynamic media show drivable by semantics

We demonstrate a system to generate dynamic media shows that are significantly richer than static slide shows, which are currently the most popular form of photo playback. The goal is to enable media reliving experiences that are aesthetically pleasing, interactive, and semantically drivable as they center on people, locations, time, and events discovered in a media collection. Dynamic shows allow for better sharing of ones media collections in diverse social networks because people have different time availabilities and perspectives, and hence may want to interact, customize, and reroute the media flow per their individual needs.

Robust face recognition based on motion pursuit

Robust face recognition is an important research area that has a great impact in the field of surveillance and human-computer interactions in general. This paper addresses how the concept of motion pursuit can bridge the alignment information with imagery similarities to form a joint decision for the purpose of robust face recognition. More explicitly, we perform multi-scale correspondence matching in a wavelet domain and utilize a simple motion measure in conjunction with wavelet response matching to form a discriminative face similarity measure. We demonstrate the efficacy of the proposed approach with a large consumer image database of diverse image capture conditions.