Part-Based Description And Recognition Of Objects In Line Drawings

After more than twenty years, the field of computer vision has still not produced any clear understanding of how fast and generic recognition of unexpected 3D objects from single 2D views is even possible. RBC, a human image understanding theory, has been recently proposed as a model of this complex high-level visual capability. However, no systematic computational evaluation of its many aspects has yet been reported. The PARVO system discussed in this paper is a first step towards this goal since its design respects and makes explicit the main assumptions of the proposed theory. It analyses single-view 2D line drawings of 3D objects typical of the ones used in human image understanding studies. It is designed to handle partially occluded objects of different shape and dimension in various spatial orientations and locations in the image plane. PARVO is able to successfully compute generic descriptions and then recognize many common man-made objects. We present an overview of PARVO and original object recognition results.