92 resultados para chaotic and diffusive motion
Resumo:
An enhanced physical model of the bowed string presented previously [1] is explored. It takes into account: the width of the bow, the angular motion of the string, bow-hair elasticity and string bending stiffness. The results of an analytical investigation of a model system - an infinite string sticking to a bow of finite width and driven on one side of the bow - are compared with experimental results published by Cremer [2] and reinterpreted here. Comparison shows that both the width of the bow and the bow-hair elasticity have a large impact on the reflection and transmission behaviour. In general, bending stiffness plays a minor role. Furthermore, a method of numerical simulation of the stiff string bowed with a bow of finite width is presented along with some preliminary results.
Resumo:
We propose an algorithm for semantic segmentation based on 3D point clouds derived from ego-motion. We motivate five simple cues designed to model specific patterns of motion and 3D world structure that vary with object category. We introduce features that project the 3D cues back to the 2D image plane while modeling spatial layout and context. A randomized decision forest combines many such features to achieve a coherent 2D segmentation and recognize the object categories present. Our main contribution is to show how semantic segmentation is possible based solely on motion-derived 3D world structure. Our method works well on sparse, noisy point clouds, and unlike existing approaches, does not need appearance-based descriptors. Experiments were performed on a challenging new video database containing sequences filmed from a moving car in daylight and at dusk. The results confirm that indeed, accurate segmentation and recognition are possible using only motion and 3D world structure. Further, we show that the motion-derived information complements an existing state-of-the-art appearance-based method, improving both qualitative and quantitative performance. © 2008 Springer Berlin Heidelberg.
Resumo:
A diffuse interface phase field model is proposed for the unified analysis of diffusive and displacive phase transitions under nonisothermal conditions. Two order parameters are used for the description of the phenomena: one is related to the solute mass fraction and the other to the strain. The model governing equations come from the balance of linear momentum, the solute mass balance (which will lead to the Cahn-Hilliard equation) and the balance of internal energy. Thermodynamic restrictions allow to define constitutive relations for the thermodynamic forces and for the mechanical and chemical dissipations. Numerical tests carried out at different values of the initial temperature show that the model is able to describe the main features of both the displacive and the diffusive phase transitions, as well as their effect on the temperature. © 2010, Advanced Engineering Solutions.
Resumo:
Optical motion capture systems suffer from marker occlusions resulting in loss of useful information. This paper addresses the problem of real-time joint localisation of legged skeletons in the presence of such missing data. The data is assumed to be labelled 3d marker positions from a motion capture system. An integrated framework is presented which predicts the occluded marker positions using a Variable Turn Model within an Unscented Kalman filter. Inferred information from neighbouring markers is used as observation states; these constraints are efficient, simple, and real-time implementable. This work also takes advantage of the common case that missing markers are still visible to a single camera, by combining predictions with under-determined positions, resulting in more accurate predictions. An Inverse Kinematics technique is then applied ensuring that the bone lengths remain constant over time; the system can thereby maintain a continuous data-flow. The marker and Centre of Rotation (CoR) positions can be calculated with high accuracy even in cases where markers are occluded for a long period of time. Our methodology is tested against some of the most popular methods for marker prediction and the results confirm that our approach outperforms these methods in estimating both marker and CoR positions. © 2012 Springer-Verlag.