Three‐dimensional object recognition using stereo vision

We propose a new method to recognize 3D objects using segment-based stereo vision. This method is available not only for polyhedra but also for objects with free-form boundaries. Predefined object models are compared with 3D boundaries extracted by segment-based stereo vision. The object models consist of local shapes and the whole shapes of the boundaries. The object models are constructed from samples of real objects or from CAD models. Based on the local shapes, candidate transformations are generated. The candidates are verified and adjusted based on the whole shapes. Experimental results show the effectiveness of the method.