Large scale 3D shape retrieval by exploiting multi-core and GPU
نویسنده
چکیده
this paper addresses the problem of 3D shape retrieval in large databases of 3D objects (large retrieval). While this problem is emerging and interesting as the size of 3D object databases grows rapidly, the main two issues the community has to focus on are: computational efficiency of 3D object retrieval and the quality of retrieved results. In this work we deal with the first consideration, namely the computational efficiency of 3D object retrieval by exploiting new implementations based on parallel computing by exploiting multi-core and GPU architectures. Experimental results, show that the large scale retrieval can be achieved using the multi-core environment.
منابع مشابه
SHREC ’ 16 Track Large - Scale 3 D Shape Retrieval from ShapeNet Core 55
With the advent of commodity 3D capturing devices and better 3D modeling tools, 3D shape content is becoming increasingly prevalent. Therefore, the need for shape retrieval algorithms to handle large-scale shape repositories is more and more important. This track aims to provide a benchmark to evaluate large-scale shape retrieval based on the ShapeNet dataset. We use ShapeNet Core55, which prov...
متن کامل3D Models Recognition in Fourier Domain Using Compression of the Spherical Mesh up to the Models Surface
Representing 3D models in diverse fields have automatically paved the way of storing, indexing, classifying, and retrieving 3D objects. Classification and retrieval of 3D models demand that the 3D models represent in a way to capture the local and global shape specifications of the object. This requires establishing a 3D descriptor or signature that summarizes the pivotal shape properties of th...
متن کاملAccelerating Bag-of-Features SIFT Algorithm for 3D Model Retrieval
We have previously proposed a shape-based 3D model retrieval algorithm that compares 3D shape based on local visual features. The method first computes a set of multi-scale local visual features from a set of depth images rendered from multiple view orientations about the 3D model. Thousands of visual features per model are integrated into a feature vector for the model by using so-called bag-o...
متن کاملMulti-View 3D Geometry Reconstruction: Exploiting Massive Parallelism
3D geometric reconstruction from digital images captured from consumer cameras is an inexpensive, but computationally demanding application. In this experimental study, we have explored parallelism in the best known public domain software (Bundler and PMVS2) and found that massive parallelism exists at various levels that can be exploited on various computer architectures (such as multi-cores, ...
متن کاملA comparison of 3D shape retrieval methods based on a large-scale benchmark supporting multimodal queries
Large-scale 3D shape retrieval has become an important research direction in content-based 3D shape retrieval. To promote this research area, two Shape Retrieval Contest (SHREC) tracks on large scale comprehensive and sketch-based 3D model retrieval have been organized by us in 2014. Both tracks were based on a unified large-scale benchmark that supports multimodal queries (3D models and sketch...
متن کامل