This course is designed to demonstrate the use of the FCam, an Application Programming Interface (API) which allows for easy and precise control of camera systems. It lets programmers implement advanced computational photography applications. Such applications even allow the modification of basic camera routines such as metering, which are hidden inside black boxes in most camera systems. FCam is also an excellent tool for teaching and research on interactive mobile computational photography.The API has been open-sourced, and is currently implemented for Nokia N900 and an experimental Frankencamera (the F2).The Frankencamera architecture for computational cameras was presented at SIGGRAPH 2010. By end-2011, the FCam will hopefully be available on Nokia™ Linux phones, Nvidia™ Tegra 3 development boards, and F3, the next version of the Stanford experimental camera. The F3 will be distributed to research universities within the US along with courseware in a National Science Foundation (NSF)-sponsored project. Nvidia Tegras and Nokia™ Linux phones are available globally.

Level
Beginner

Intended Audience
Researchers and educators interested in computational photography.

Prerequisites
Ability to read C++ code.

Course Schedule
Session 1: 14:15-15:45
14:15-14:45 Kari Pulli: Introduction to mobile computation photography, FCam motivation and architecture.
14:45-15:45 Alejandro Troccoli: Programming with FCam, anatomy of FCam.

Break:15:45-16:00

Session 2: 16:00-18:00
16:00-16:25 Alejandro Troccoli: Image processing using OpenGL and ARM Neon.
16:25-17:00 Timo Ahonen: FCamera, a point and shoot camera app.
17:00-17:35 Timo Ahonen: FCam applications: low-light capture, HDR, focus-stacks
17:30-18:00 Kari Pulli: Future and wrap&up

Presenter(s)
Kari Pulli has worked on visual computing for 20 years. He has been a Senior Director of Research at Nvidia since April 2011, following an appointment as Nokia Fellow at Nokia Research Center. He previously organized and taught courses on mobile 3D graphics both at SIGGRAPH and Eurographics conferences, and has taught graphics and imaging at University of Oulu and Stanford University. He earned a PhD in Computer Science at University of Washington, was a research associate at Stanford University, and a visiting scientist at Massachusetts Institute of Technology.

Timo Ahonen received a PhD (with Honors) in Information Engineering in 2009 from the University of Oulu and is now a Senior Researcher at Nokia Research Center, Palo Alto. He is currently working on computational photography on mobile devices. His research interests include computational photography, computer vision, object and face recognition, and image processing. He has authored several international journal and conference papers on texture feature extraction and its application in face image analysis. He also often reviews papers submitted to the major journals and conferences in computer vision. He visited the Swiss Federal Institute of Technology in 2002 and University of Maryland in 2005.

Alejandro Troccoli has been with Nvidia since 2006 and joined Nvidia Research as a Senior Research Scientist in March 2011 to work in mobile computer vision and applications. As a 3D Systems Software Engineer he lead the development of Nvidia's Optimus technology, contributed to Nvidia's hybrid technology and did development work for the Direct3D driver. Alejandro received a Licenciatura en Ciencias de la Computacion from the Universidad de Buenos Aires in 2001. He did his graduate work at Columbia University, where he received a PhD in 2006.