Free-Form 3D Object Recognition In Range Data Using Weak Correspondence Between Local Features

Model-Based 3D object recognition systems have a variety of potential applications, but widespread use of such systems has not occurred, due to a number of factors including the representational limitations of models. This has led to systems that recognize objects of free-form shape. The system described in this paper recognizes such free-form objects in dense range data acquired by a structured light rangefinder. Images and object models are represented as a network of salient segments which are then brought into correspondence until a reliable pose estimate is available. Experiments with a database of images and object models highlight the contributions of this system.