Generalized Autofocus
IEEE Workshop on Applications of Computer Vision (WACV'11)
Kona, Hawaii, 2011

Abstract
All-in-focus imaging is a computational photography technique that
produces images free of defocus blur by capturing a stack of images focused
at different distances and merging them into a single sharp result. Current
approaches assume that images have been captured offline, and that a
reasonably powerful computer is available to process them. In contrast, we
focus on the problem of how to capture such input stacks in an efficient and
scene-adaptive fashion. Inspired by passive autofocus techniques, which
select a single best plane of focus in the scene, we propose a method to
automatically select a minimal set of images, focused at different depths,
such that all objects in a given scene are in focus in at least one image.
We aim to minimize both the amount of time spent metering the scene and
capturing the images, and the total amount of high-resolution data that is
captured. The algorithm first analyzes a set of low-resolution sharpness
measurements of the scene while continuously varying the focus distance of
the lens. From these measurements, we estimate the final lens positions
required to capture all objects in the scene in acceptable focus. We
demonstrate the use of our technique in a mobile computational photography
scenario, where it is essential to minimize image capture time (as the camera
is typically handheld) and processing time (as the computation and energy
resources are limited).
Paper
Download the paper in PDF format.
Video
Download a video demo of our system.
Presentation Slides
Download the PowerPoint slides of the WACV 2011 talk.
Citation
Daniel Vaquero, Natasha Gelfand, Marius Tico, Kari Pulli, and Matthew Turk. Generalized Autofocus. In IEEE Workshop on Applications of Computer Vision (WACV'11), Kona, Hawaii, January 2011.
BibTeX Entry
@InProceedings{VaqueroWACV2011,
author = {Daniel Vaquero and Natasha Gelfand and Marius Tico and Kari Pulli and Matthew Turk},
title = {Generalized Autofocus},
booktitle = {IEEE Workshop on Applications of Computer Vision (WACV'11)},
address = {Kona, Hawaii},
month = {January},
year = {2011}
}
Related Publications
- Daniel Vaquero, Natasha Gelfand, Marius Tico, Kari Pulli, and Matthew Turk. Efficient and Scene-Adaptive Capture of Focal Stacks. In Fifth Graduate Student Workshop on Computing (GSWC'10), Santa Barbara, California, October 2010. (extended abstract, received the 2nd best paper award)