With the increasing popularity of 3D applications such as computer games, a lot of 3D geometry models are being created. To encourage sharing and reuse, techniques that support matching and retrieval of these models are emerging. However, only a few of them can handle deformable models, that is, models of different poses, and these methods are generally very slow. In this paper, we present a no...

Deformable surface models provide a very attractive method for segmenting the three-dimensional shape of complex and various internal organs from volumetric medical images. However, although researchers have succeeded in overcoming some of the limitations of this approach, there still exist several significant unsolved problems. In this paper, we propose a multi-featured multi-scale deformable ...

Recent research topics deal with the problem how to reconstruct real-world objects from a set of multiple range images showing only portions of the object. Here we present an approach how to generate and adapt a geometrical deformable model (GDM) to a set of already registered range images in order to reconstruct the complete object. From the range images we derive a signed distance function wh...

We present an interface between a deformable body mechanics model and a rigid body mechanics model. What is novel with our approach is that the physical representation in both the models is the same, which ensures behavioral correctness and allows great flexibility. We use a massspring representation extended with the concept of volume, and thus contact and collision. All physical interaction o...

In this work we consider an adaptive optical system in which a deformable mirror is controlled to compensate for random wavefront disturbances. For most systems of this type, the shape of the mirror is taken as a linear function of the wavefront error, leading to satisfactory results in linear regimes. Here, the geometric shape of the mirror leading to a perfect correction of the wavefront is d...

Convolutional neural networks (CNNs) have demonstrated their ability object detection of very high resolution remote sensing images. However, CNNs have obvious limitations for modeling geometric variations in remote sensing targets. In this paper, we introduced a CNN structure, namely deformable ConvNet, to address geometric modeling in object recognition. By adding offsets to the convolution l...

This paper presents an original problem of knot detection in 3D X-ray Computer Tomography images of wood stems. This image type is very different from classical medical images and presents specific geometric structures. These ones are characteristic of wood stems nature. The contribution of this work is to exploit the original geometric structures in a simple and fast algorithm to automatically...

PURPOSE The spatial normalization and registration of tomographic images from different subjects is a major problem in several medical imaging areas, including functional image analysis, morphometrics, and computer-aided neurosurgery. The focus of this article is the development of a computerized methodology for the spatial normalization of 3D images. METHOD We propose a technique that is bas...

Haptics is an increasingly common modality in human-computer interfacing. The focus of this paper is the problem arising from the difference between the high sampling rate requirements of haptic interfaces and the significantly lower update rates for physical models simulated in virtual environments. This is a critical problem, especially for applications involving haptic manipulation of deform...