Abstract. The problem of searching for a model-based scene interpretation is analyzed within a probabilistic framework. Object models are formulated as generative models for range ...
Abstract. We present a novel model for object recognition and detection that follows the widely adopted assumption that objects in images can be represented as a set of loosely cou...
Thomas Deselaers, Andre Hegerath, Daniel Keysers, ...
− We propose a vision based 3D object recognition and tracking system, which provides high level scene descriptions such as object identification and 3D pose information. The sys...
In this paper we will show how constraint solving methods can be applied for the recognition of buildings in aerial images. Object models are transformed to constraint representati...
We present a discriminative part-based approach for the recognition of object classes from unsegmented cluttered scenes. Objects are modeled as flexible constellations of parts co...