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In this paper we target the problem of the retrieval of colour patterns over surfaces. We generalize to surface tessellations the well known Local Binary Pattern (LBP) descriptor for images. The key concept of the LBP is to code the variability of the ...

Content-based querying of 3D object collections has the intrinsic difficulty of creating the query object and previous approaches have concentrated in producing global simplifications such as sketches. In contrast, in this paper, the concept of querying ...

We present an automatic approach for the retrieval of a complex structure within a 3D digital volume, using a generic deformable surface model. We apply this approach to the inner ear reconstruction of Cone Beam CT(CBCT) 3D data. The proposed method is ...

In light of the increased processing power of graphics cards and the availability of large-scale datasets, deep neural networks have shown a remarkable performance in various visual computing applications. In this paper, we propose a geometric framework ...

Sketch-based 3D model retrieval has the intuitiveness advantage over other types of retrieval schemes. Currently, there is a lot of research in sketch-based 3D model retrieval, which usually targets the problem of retrieving a list of candidate 3D ...

2D scene image-based 3D scene retrieval is a new research topic in the field of 3D object retrieval. Given a 2D scene image, it is to search for relevant 3D scenes from a dataset. It has an intuitive and convenient framework which allows users to learn, ...

Recent advances in consumer-grade depth sensors have enable the collection of massive real-world 3D objects. Together with the rise of deep learning, it brings great potential for large-scale 3D object retrieval. In this challenge, we aim to study and ...

Proteins are macromolecules central to biological processes that display a dynamic and complex surface. They display multiple conformations differing by local (residue side-chain) or global (loop or domain) structural changes which can impact ...

This paper presents the results of the SHREC'18 track: Retrieval of gray patterns depicted on 3D models. The task proposed in the contest challenges the possibility of retrieving surfaces with the same texture pattern of a given query model. This task, ...

This track of the SHREC 2018 originally aimed at recognizing relief patterns over a set of triangle meshes from laser scan acquisitions of archaeological fragments. This track approaches a lively and very challenging problem that remains open after the ...

In this paper, we propose a new architecture of 3D deep neural network called 3D Hahn Moments Convolutional Neural Network (3D HMCNN) to enhance the classification accuracy and reduce the computational complexity of a 3D pattern recognition system. The ...

Archaeological artifacts are an important part of our cultural heritage. They help us understand how our ancestors used to live. Unfortunately, many of these objects are badly damaged by the passage of time and need repair. If the object exhibits some ...

In the typical approach, person re-identification is performed using appearance in 2D still images or videos, thus invalidating any application in which a person may change dress across subsequent acquisitions. For example, this is a relevant scenario ...

In the Visual Heritage domain, search engines are expected to support archaeologists and curators to address cross-correlation and searching across multiple collections. Archaeological excavations return artifacts that often are damaged with parts that ...

Image convolution with a filtering mask is at the base of several image analysis operations. This is motivated by Mathematical foundations and by the straightforward way the discrete convolution can be computed on a grid-like domain. Extending the ...