Deep learning has recently gained popularity achieving state-of-the-art performance in tasks
involving text, sound, or image processing. Due to its outstanding performance, there have …

We present a novel 3D shape descriptor that uses a set of panoramic views of a 3D object
which describe the position and orientation of the object's surface in 3D space. We obtain a …

We present a 3D shape retrieval methodology based on the theory of spherical harmonics.
Using properties of spherical harmonics, scaling and axial flip** invariance is achieved …

This work offers an overview of the state-of-the-art on the emerging area of 3D object
retrieval based on partial queries. This research area is associated with several application …

This paper presents a unified framework for 3D shape retrieval. The method supports
multimodal queries (2D images, sketches, 3D objects) by introducing a novel view-based …

Environment analysis of automatic vehicles needs the detection from 3-D point cloud
information. This paper addresses this task when only partial scanning data are available …

The success of object recognition and retrieval is largely determined by data representation.
A good feature descriptor can detect the high-level abstraction of objects, which contains …

We address content-based retrieval of complete 3D object models by a probabilistic
generative description of local shape properties. The proposed shape description framework …

Content-based shape retrieval techniques can facilitate 3D model resource reuse, 3D model
modeling, object recognition, and 3D content classification. Recently more and more …

We present a novel 3D object retrieval method that relies upon a hybrid descriptor which is
composed of 2D features based on depth buffers and 3D features based on spherical …