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.