Subobject detection through spatial relationships on mobile phones

Abstract

We present a novel image classification technique for detecting multiple objects (called subobjects) in a single image. In addition to image classifiers, we apply spatial relationships among the subobjects to verify and to predict locations of detected and undetected subobjects, respectively. By continuously refining the spatial relationships throughout the detection process, even locations of completely occluded exhibits can be determined. This approach is applied in the context of PhoneGuide, an adaptive museum guidance system for camera-equipped mobile phones. Laboratory tests as well as a field experiment reveal recognition rates and performance improvements when compared to related approaches.