摘要
Defining a compact and robust shape descriptor is the most important issue in 3D shape retrieval. This paper proposes a new shape descriptor called Poisson histogram, which can capture shape structure feature very well. Moreover, it is robust under different geometry processing and has low feature dimension for efficient indexing. Poisson histogram can be defined by the following two steps. Firstly, we use Poisson equation to define a 3D shape signature. Secondly, we derive a histogram-based shape descriptor by accumulating the values of the defined signature in bins. To verify the performance of Poisson histogram, we perform an experimental comparison on McGill database of 3D shapes. Results show that Poisson histogram is better than several existing histogram-based shape descriptors both in retrieving accuracy and retrieving efficiency.
- 出版日期2011-4-15
- 单位浙江工业大学