3-D object recognition using functional models

Many human activities are based on visual recognition of a scene. Development of scene recognition capability on computer is essential to the development of an intelligent robot. This paper proposes a three-dimensional (3-D) object recognition system using functional models. In conventional geometric model-based recognition, one reference model must be provided for each possible object shape in the same category. This paper proposes a functional model that will allow flexibility in representation of objects belonging to the same category. Experiments were conducted to provide measurement data for demonstrating this functional model-based object recognition technique. Scene segmentation uses both gray scale image and range image to provide superior segmentation results. The performance of a functional model-based method for recognizing objects with different shapes that belong to the same functional category is demonstrated.