17. A. Opelt, A. Pinz, A. Zisserman: Fusing shape and appearance information for object category detection
We present methods for recognizing object categories which
are able to combine various feature types (e.g. image patches and edge boundaries).
Our
objective is to detect object instances in an image, as opposed to the easier
task of image categorization. To this end, we investigate two algorithms for
learning and detecting object categories which both benefit from combining
features. The first uses a naive combination method for detectors each employing
only one type of feature, the second learns the best features (from a
pool of patches and boundaries).
In experiments we achieve comparable results to the state of the art over a
number of datasets, and for some categories we even achieve the lowest errors
that have been reported so far. The results also show that certain object categories
prefer certain feature types (e.g. boundary fragments for airplanes).
poster.pdf