Indoor-Outdoor Detector for Mobile Phone Cameras Using Gentle Boosting

We developed a new compact indoor-outdoor detector
suitable for an embedded digital camera in a mobile
phone. The detector works on a Bayer domain image
before applying white balance gains. The key idea is to
use a small number of photometrical and colorimetrical
features typically calculated in the mobile phone cameras
for white balance gains evaluation. These features are
collected using an annotated image database that was
captured using the camera for a variety of indoor and
outdoor scenes by different customers. Using this
database, a gentle boosting classifier for indoor-outdoor
detection is designed and evaluated. An optimal feature
subset and optimal number of rounds are selected as well.
On a set of 3,176 images, the proposed detector achieves a
1.7% error rate for indoor and 10.8% for outdoor scenes.
A comparative study versus a number of known embedded
indoor-outdoor detectors shows advantages of the
proposed indoor-outdoor detector for mobile phone
cameras.