2 research outputs found
Quasi Spin Images
The increasing adoption of 3D capturing equipment, now also found in mobile devices, means that 3D content is increasingly prevalent. Common operations on such data, including 3D object recognition and retrieval, are based on the measurement of similarity between 3D objects. A common way to measure object similarity is through local shape descriptors, which aim to do part-to-part matching by describing portions of an object's shape. The Spin Image is one of the local descriptors most suitable for use in scenes with high degrees of clutter and occlusion but its practical use has been hampered by high computational demands. The rise in processing power of the GPU represents an opportunity to significantly improve the generation and comparison performance of descriptors, such as the Spin Image, thereby increasing the practical applicability of methods making use of it. In this paper we introduce a GPU-based Quasi Spin Image (QSI) algorithm, a variation of the original Spin Image, and show that a speedup of an order of magnitude relative to a reference CPU implementation can be achieved in terms of the image generation rate. In addition, the QSI is noise free, can be computed consistently, and a preliminary evaluation shows it correlates well relative to the original Spin Image
Radial Intersection Count Image: a Clutter Resistant 3D Shape Descriptor
A novel shape descriptor for cluttered scenes is presented, the Radial
Intersection Count Image (RICI), and is shown to significantly outperform the
classic Spin Image (SI) and 3D Shape Context (3DSC) in both uncluttered and,
more significantly, cluttered scenes. It is also faster to compute and compare.
The clutter resistance of the RICI is mainly due to the design of a novel
distance function, capable of disregarding clutter to a great extent. As
opposed to the SI and 3DSC, which both count point samples, the RICI uses
intersection counts with the mesh surface, and is therefore noise-free. For
efficient RICI construction, novel algorithms of general interest were
developed. These include an efficient circle-triangle intersection algorithm
and an algorithm for projecting a point into SI-like (, )
coordinates. The 'clutterbox experiment' is also introduced as a better way of
evaluating descriptors' response to clutter. The SI, 3DSC, and RICI are
evaluated in this framework and the advantage of the RICI is clearly
demonstrated.Comment: 18 pages, 16 figures, to be published in Computers & Graphic