Locating object contours in complex background using improved snakes

An active contour model, called snake, can adapt to object boundary in an image. A snake is defined as an energy minimizing spline guided by external constraint forces and influenced by image forces that pull it toward features such as lines or edges. The traditional snake model fails to locate object contours that appear in complex background. In this paper, we present an improved snake model associated with new regional similarity energy and a gravitation force field to attract the snake approaching the object contours efficiently. Experiment results show that our snake model works successfully for convex and concave objects in a variety of complex backgrounds.     

A semi-automatic system for edge tracking with snakes

Active contour models, or snakes, developed in (Kass et al. 1988), use a simple physical model to track edges in image sequences. Snakes as originally defined however, tend to shrink, stretch and slide back and forth in unwanted ways along a tracked edge and are also confused by multiple edges, always grabbing the nearest one. In this paper a semi-automatic system is presented that combines motion estimation techniques with snakes to overcome these problems. An algorithm is presented that uses a block matching technique to guide the endpoints of the snake, optical flow to push the snake in the direction of the underlying motion, followed by the traditional snake edge-fitting minimization process. We use this technique for tracking facial features of an actor for driving computer animated characters.     

改进GVF的自动Snakes模型

针对Gradient vector field Snakes模型轮廓线需人工初始化的问题及GVF场强分布不合理所导致的模型效率低下和角点定位精度低的问题,在分析GVF场强分布和模型迭代变形原理的基础上,改进原始GVF Snakes模型:模型以SUSAN算法提取的边缘点集构建GVF Snakes模型的初始化轮廓线;并依据图像SUSAN边缘线和模型迭代变形原理局部修正和整体调整GVF场强分布,以符合模型高效迭代变形和对角点、细边缘精确定位的需要。理论分析和实验结果表明,改进GVF的自动Snakes模型提高了模型的计算效率,对细边缘和角点有更高的定位精度。     

Snake Robot Obstacle-Aided Locomotion: Modeling, Simulations, and Experiments

Snakes utilize irregularities in the terrain, such as rocks and vegetation, for faster and more efficient locomotion. This motivates the development of snake robots that actively use the terrain for locomotion, i.e., obstacle-aided locomotion. In order to accurately model and understand this phenomenon, this paper presents a novel nonsmooth (hybrid) mathematical model for wheel-less snake robots, which allows the snake robot to push against external obstacles apart from a flat ground. The framework of nonsmooth dynamics and convex analysis allows us to systematically and accurately incorporate both unilateral contact forces (from the obstacles) and isotropic friction forces based on Coulomb's law using set-valued force laws. The mathematical model is verified through experiments. In particular, a back-to-back comparison between numerical simulations and experimental results is presented. It is, furthermore, shown that the snake robot is able to move forward faster and more robustly by exploiting obstacles.     

Control of snake robots with switching constraints: trajectory tracking with moving obstacle

We propose control of a snake robot that can switch lifting parts dynamically according to kinematics. Snakes lift parts of their body and dynamically switch lifting parts during locomotion: e.g. sinus-lifting and sidewinding motions. These characteristic types of snake locomotion are used for rapid and efficient movement across a sandy surface. However, optimal motion of a robot would not necessarily be the same as that of a real snake as the features of a robot’s body are different from those of a real snake. We derived a mathematical model and designed a controller for the three-dimensional motion of a snake robot on a two-dimensional plane. Our aim was to accomplish effective locomotion by selecting parts of the body to be lifted and parts to remain in contact with the ground. We derived the kinematic model with switching constraints by introducing a discrete mode number. Next, we proposed a control strategy for trajectory tracking with switching constraints to decrease cost function, and to satisfy the conditions of static stability. In this paper, we introduced a cost function related to avoidance of the singularity and the moving obstacle. Simulations and experiments demonstrated the effectiveness of the proposed controller and switching constraints.     

Segmentation of the left ventricle in cardiac cine MRI using a shape-constrained snake model

Segmentation of the left ventricle (LV) is a hot topic in cardiac magnetic resonance (MR) images analysis. In this paper, we present an automatic LV myocardial boundary segmentation method using the parametric active contour model (or snake model). By convolving the gradient map of an image, a fast external force named gradient vector convolution (GVC) is presented for the snake model. A circle-based energy is incorporated into the GVC snake model to extract the endocardium. With this prior constraint, the snake contour can conquer the unexpected local minimum stemming from artifacts and papillary muscle, etc. After the endocardium is detected, the original edge map around and within the endocardium is directly set to zero. This modified edge map is used to generate a new GVC force filed, which automatically pushes the snake contour directly to the epicardium by employing the endocardium result as initialization. Meanwhile, a novel shape-similarity based energy is proposed to prevent the snake contour from being strapped in faulty edges and to preserve weak boundaries. Both qualitative and quantitative evaluations on our dataset and the publicly available database (e.g. MICCAI 2009) demonstrate the good performance of our algorithm.     

MAC: magnetostatic active contour model

We propose an active contour model using an external force field that is based on magnetostatics and hypothesized magnetic interactions between the active contour and object boundaries. The major contribution of the method is that the interaction of its forces can greatly improve the active contour in capturing complex geometries and dealing with difficult initializations, weak edges and broken boundaries. The proposed method is shown to achieve significant improvements when compared against six well-known and state-of-the-art shape recovery methods, including the geodesic snake, the generalized version of GVF snake, the combined geodesic and GVF snake, and the charged particle model.     

一种基于Snakes方法的人脸五官几何特征提取新算法

本文对传统Snakes方法的能量函数进行了改进：增加了对Snakes曲线进行形状限定的能量项，用来约束Snakes曲线变化时的形状，使之更容易与相应人脸特征吻合；改进了其中的图像能量项，采用图像颜色色度梯度取代图像灰度梯度构造图像能量项，由于色度梯度体现了颜色的本质信息，这种改进有利于Snakes曲线正确收敛于颜色本质差异大的的地方即图像真实轮廓处。实验结果表明，改进后的Snakes用于人脸特征提取鲁棒性强。     

Boundary vector field for parametric active contours

Snakes are widely used in the fields of computer vision and image processing. There are a number of shortcomings of the traditional snakes, including the capture range problem and the concave object extraction problem. Gradient vector flow snake enhances the concave object extraction capability. However, it suffers from high computational requirement. In this paper, we present a new external force which is generated by a novel interpolation scheme which reduces the computational requirement significantly, and at the same time, improves the capture range and concave object extraction capability.     

Influence of the gradient of a slope on optimal locomotion curves of a snake-like robot

Snakes perform many kinds of movement adapted to different environments. Utilizing the snake as a model, we have developed a two-dimensional snake-like robot that emulates a snakes' function. To make our robot move optimally while adapting to the slope of the environment, in this study we discuss the influence of the gradient of a slope on the creeping locomotion of the robot and derive optimal creeping locomotion curves that adapted to the given slopes.