On geometric and soft shape content-based search

This paper proposes a probabilistic framework for enhancing the recognition performance of 3D object queries based on soft shape descriptors, such as volume, surface and convexity. The goal is to improve the initial ranking results of pure geometry-based algorithms by capitalizing on the discriminative power of objects with close values on the so-called “soft shape descriptor”. The proposed method has been applied to benchmarking 3D object databases providing promising results demonstrating a clear improvement on the precision/recall ratio.