Local Representations for Multi-object Recognition

Methods for the recognition of multiple objects in images using local representations are introduced. Starting from a straight forward approach, we combine the use of local representations with region segmentation and template matching. The performance of the classifiers is evaluated on four image databases of different difficulties. All databases consist of images containing one, two or three objects and differ in the backgrounds which are used. Also, the presence or absence of occlusions of the objects in the scenes is considered. Classification results are promising regarding the difficulty of the task.