Skeleton Extraction Method Research Articles

Extracting curve-skeletons from digital shapes using occluding contours

Curve-skeletons are compact and semantically relevant shape descriptors, able to summarise both topology and pose of a wide range of digital objects. Most of the state-of-the-art algorithms for their computation rely on the type of geometric primitives used and sampling frequency. In this paper, we introduce a formally sound and intuitive definition of a curve-skeleton, then we propose a novel method for skeleton extraction that relies on the visual appearance of the shapes. To achieve this result, we inspect the properties of occluding contours, showing how information about the symmetry axes of a 3D shape can be inferred from a small set of its planar projections. The proposed method is fast, insensitive to noise and resolution, capable of working with different shape representations, and easy to implement.

Robust curve skeleton extraction for vascular structures

Extracting curve skeletons for vascular structures is vital for many medical applications. However, most of existing curve skeleton extraction methods are either too complicated or not robust to be applied directly on vascular meshes. In this paper, we present a simple and robust three-step approach for one-dimensional curve skeleton extraction for vascular models. Firstly, the given vascular mesh is iteratively contracted until it is thin enough. Then the contracted mesh is further subdivided. Thereafter our approach proceeds over the point cloud domain yielded by the vertices of the subdivided mesh. Secondly, the joint and branch points of the model are detected. Finally, a skeleton growing procedure is proposed to generate the curve skeleton. Experimental results show that our approach is robust for vascular structures of any topology, e.g. with or without loops or with nearby structures. Additional experiments demonstrate that our approach can be extended to handle other common shapes.

Skeleton-based Adaptive In-between Generation for Hand-drawn Key Frames

For improving the efficiency of 2D animation production, this paper presents a method to create in-between frames based on hand-drawn key-frames. The outlines of characters or objects on two key-frames are used as inputs. First, a skeleton linkage of the target object is automatically constructed by rasterizing each of input key-frames and then applying a pixel-based skeleton extraction method. Secondary, a pair of skeleton linkages having corresponding structure between the current key-frame and the next key-frame is constructed by applying the stroke matching algorithm. After these processes, motion transitions between the skeleton linkages are generated based on our simulation model. When the in-between frames are created only in the 2D plane, the outlines at in-between frames can be generated by a 2D deformation. In case that the in-between transitions are containing a rotation around an axis which is no perpendicular to the drawing plane, however, a 3D structure is required. For achieving such in-between transitions, our method constructs a 3D structure by inflating 2D mesh based on the input outlines. Finally, the contours from the view-point for the created 3D structure are projected onto the 2D plane during in-between transitions. In our method, we adopt the Photic Extremum Lines (PEL) to extract the 2D contours from the obtained 3D shape. In this way, we achieve the in-between creation containing spatial rotation such as hand-flipping, which has not been achieved by general ways of in-between creation method.

3D Model Skeleton Extraction Based on Poisson Equation

Existing skeleton extraction methods, however, are often sensitive to noises and disconnected. This paper proposed a skeleton extraction method based on Poisson equation. It can approximate the topology structure of the input 3D model well, and avoid the broken lines. First, the proposed method extracts critical points of a 3D model by using Poisson equation and geodesic distance. Then the extracted critical points are connected and star skeleton of the 3D model is defined. Finally, the reverse force filed based Poisson energy distribution is used to push star skeleton into final result. Experiments show that the extracted skeleton is continuous and has no small branches affected model noises.

A mobile environment for sketching-based skeleton generation

Articulated character animation is typically performed by manually creating and rigging a skeleton into an unfolded 3D object. However, such tasks are not trivial, as they require a substantial amount of training and practices. Although automatic skeleton extraction methods have been proposed, they generally may not guarantee that the resulting skeleton can help produce desired animations according to user intention. In this paper, we present a sketching-based skeleton generation method suitable for use in the mobile environment. This method takes user sketching as an input, and based on the mesh segmentation result of a 3D object, it estimates a skeleton for articulated character animation. In addition, we are currently developing a Web-based mobile platform to support mesh editing by a group of collaborative users and we depict the system architecture of such a platform. Results show that our method can produce better skeletons in terms of joint positions and topological structure.

3D reconstruction and dynamic modeling of root architecture in situ and its application to crop phosphorus research

Root architecture plays important roles in plant water and nutrient acquisition. However, accurate modeling of the root system that provides a realistic representation of roots in the soil is limited by a lack of appropriate tools for the non-destructive and precise measurement of the root system architecture in situ. Here we describe a root growth system in which the roots grow in a solid gel matrix that was used to reconstruct 3D root architecture in situ and dynamically simulate its changes under various nutrient conditions with a high degree of precision. A 3D laser scanner combined with a transparent gel-based growth system was used to capture 3D images of roots. The root system skeleton was extracted using a skeleton extraction method based on the Hough transformation, and mesh modeling using Ball-B spline was employed. We successfully used this system to reconstruct rice and soybean root architectures and determine their changes under various phosphorus (P) supply conditions. Our results showed that the 3D root architecture parameters that were dynamically calculated based on the skeletonization and simulation of root systems were significantly correlated with the biomass and P content of rice and soybean based on both the simulation system and previous reports. Therefore, this approach provides a novel technique for the study of crop root growth and its adaptive changes to various environmental conditions.

Skeleton extraction by mesh contraction

Extraction of curve-skeletons is a fundamental problem with many applications in computer graphics and visualization. In this paper, we present a simple and robust skeleton extraction method based on mesh contraction. The method works directly on the mesh domain, without pre-sampling the mesh model into a volumetric representation. The method first contracts the mesh geometry into zero-volume skeletal shape by applying implicit Laplacian smoothing with global positional constraints. The contraction does not alter the mesh connectivity and retains the key features of the original mesh. The contracted mesh is then converted into a 1D curve-skeleton through a connectivity surgery process to remove all the collapsed faces while preserving the shape of the contracted mesh and the original topology. The centeredness of the skeleton is refined by exploiting the induced skeleton-mesh mapping. In addition to producing a curve skeleton, the method generates other valuable information about the object's geometry, in particular, the skeleton-vertex correspondence and the local thickness, which are useful for various applications. We demonstrate its effectiveness in mesh segmentation and skinning animation.

Skeleton Primitive Extraction Method on Textures with Different Nonlinear Wavelets

Problem Statement: A novel method for dominant skeleton extraction of textures using different nonlinear wavelet transforms is proposed in this study. In the present study 3◊3 masks are used for extraction of skeleton primitives. For a 3 ◊3 skeleton primitive there will be 2 9 skeleton primitive combinations. But the present study consi dered a skeleton primitive for the skeletonization purpose if and only if its center pixel is one and skeleton primitives are represented by the corresponding skeleton primitive weight. By this, t here will be 2 8 combinations of skeleton primitives. Approach : The skeleton primitive are used for evaluating sk eleton points. The skeleton of an object has the property that it is reduced to one point wh en the skeleton primitive used for the skeletonizat ion is exactly homothetic to the object. The dominant s keleton subset is evaluated by counting the skeleto n points. The skeleton subset that leads to the least skeleton points will be the resultant skeleton sub set. The present study classified the textures based on two methods. In the first method textures are classified based on skeleton primitive weight, whic h is nothing but based on skeleton primitive combination. In the second method classification is made based on distance function of skeleton points. Results : The proposed method is applied on 24 Brodatz text ures using the three nonlinear wavelet transformed textures. By this the dominant skeleton primitive weight is obtained for each texture. Based on the number of skeleton points dis tance measures are calculated based on which texture classification is obtained. Conclusions : The two methods are applied on Brodatz textures u sing different nonlinear wavelet transforms which classi fied the textures. The first method is appropriate if one need to classify based on skeleton subsets. The second method is appropriate if the classification is to be done based on least number of skeleton points .

FORMS: A flexible object recognition and modelling system

We describe a flexible object recognition and modelling system (FORMS) which represents and recognizes animate objects from their silhouettes. This consists of a model for generating the shapes of animate objects which gives a formalism for solving the inverse problem of object recognition. We model all objects at three levels of complexity: (i) the primitives, (ii) the mid-grained shapes, which are deformations of the primitives, and (iii) objects constructed by using a grammar to join mid-grained shapes together. The deformations of the primitives can be characterized by principal component analysis or modal analysis. When doing recognition the representations of these objects are obtained in a bottom-up manner from their silhouettes by a novel method for skeleton extraction and part segmentation based on deformable circles. These representations are then matched to a database of prototypical objects to obtain a set of candidate interpretations. These interpretations are verified in a top-down process. The system is demonstrated to be stable in the presence of noise, the absence of parts, the presence of additional parts, and considerable variations in articulation and viewpoint. Finally, we describe how such a representation scheme can be automatically learnt from examples.

Fringe-orientation maps and fringe skeleton extraction by the two-dimensional derivative-sign binary-fringe method

The fringe-orientation information of an interferometric fringe pattern is provided in the form of a fringe-orientation map by spin filtering. The fringe-orientation information is an important feature of fringe patterns and is helpful in many fringe-pattern processing algorithms. With the help of a fringe-orientation map the two-dimensional derivative-sign binary-fringe method is developed to extract fringe skeletons from a fringe pattern with an arbitrary fringe distribution. This fringe skeleton extraction method does not require thresholds and a thinning process. It is relatively robust and highly accurate.