SIMD, SMP and MIMD-DM approaches for real-time 2D image stabilization

We present a real-time image stabilization method, based on a 2D motion model, and exploiting different levels of parallelism in its implementation. This stabilization method is decomposed into three parts. First, the image matching is determined by a feature-based technique. In the second part, the motion between consecutive frames is estimated and filtered to extract the unwanted motion component. Finally, these component is used to correct (warp) the images, resulting in a stable sequence. To validate our stabilization approach in a real-time on-board system context, the algorithm was implemented and tested over different hardware platforms, allowing a performance evaluation in function of the adopted architecture. In this paper, we present some results concerning the parallel implementation of the algorithm, using the SIMD ALTIVEC instructions set, a symmetric multi-processor architecture (SMP) and a MIMD-DM architecture.Nous présentons une méthode de stabilisation de séquence d'images en temps réel, basée sur un modèle de mouvement 2D, avec mise en correspondance par détection et suivi de primitives. Le déplacement estimé entre deux images est filtré afin d'isoler la composante non voulue du mouvement, et finalement utilisé pour corriger les images rendant la séquence stable. Afin de valider l'approche dans un contexte de système temps réel embarqué, l'algorithme a été implanté et testé sur plusieurs plateformes matérielles différentes, permettant l'évaluation des performances selon l'architecture adoptée. Nous montrons ici quelques résultats obtenus, concernant notamment la parallélisation de l'algorithme au moyen des instructions SIMD ALTIVEC, l'adoption d'une architecture symétrique multiprocesseur (SMP) et l'implantation sur une architecture de type MIMD-DM

Fast Video Stabilization Algorithms

A fast and robust electronic video stabilization algorithm is presented in this thesis. It is based on a two-dimensional feature-based motion estimation technique. The method tracks a small set of features and estimates the movement of the camera between consecutive frames. It is used to characterize the motions accurately including camera rotations between two imaging instants. An affine motion model is utilized to determine the parameters of translation and rotation between images. The determined affine transformation is then exploited to compensate for the abrupt temporal discontinuities of input image sequences. Also, a frequency domain approach is developed to estimate translations between two consecutive frames in a video sequence. Finally, a jitter detection technique to isolate vibration affected subsequence of an image sequence is presented. The experimental results of using both simulated and real images have revealed the applicability of the proposed techniques. In particular, the emphasis has been to develop real time implementable algorithms, suitable for unmanned vehicles with severe payload constraints

A nonlinear multiscale finite element model for comb-like sandwich panels

Modern composite materials and lightweight construction elements are increasingly replacing classic materials in practical applications of mechanical and civil engineering. Their high prevalence creates a demand for calculation methods which can accurately describe the mechanical behavior of a composite structure, while at the same time preserving moderate requirements in terms of numerical cost. Modeling the full microstructure of a composite by means of the classical finite element method quickly exceeds the capabilities of today’s hardware. The resulting equation systems would be extremely large and unsuitable for solution due to their enormous calculation times and memory requirements. Homogenization methods have been developed as a remedy to this issue, in which the complex microstructure is replaced by a homogeneous material using averaged mechanical properties that are determined via experiments or by analytical or numerical investigation. However, classical homogenization methods usually fail as soon as nonlinear system behavior is introduced and the effective properties, which are presumed to be constant, begin to change during the course of a simulation. In this work, a coupled global-local method will be presented specifically for sandwich panels with axially stiffened or honeycomb cores. Herein, a global model, in which the complete structure is discretized with standard shell elements, is coupled with multiple local models, describing the microstructure of the sandwich throughout the full thickness coordinate and using shell elements for discretization as well. The local formulation is implemented by means of a constitutive law for the global model, so that one local boundary value problem is evaluated in each integration point of the global structure. By reevaluating the local models in every iteration step in a nonlinear simulation, physical and geometrical nonlinearity can be described. For instance, it will be shown in numerical examples that elasto-plastic material behavior and pre- and postcritical buckling behavior can be described, contrary to most classical homogenization methods. Next to the derivation of theoretical fundamentals and the introduction of the coupled method as well as several numerical examples, additional chapters are detailing some issues concerning mesh generation and the implementation of a high-bandwidth data interface between global and local models

First Annual Workshop on Space Operations Automation and Robotics (SOAR 87)

Several topics relative to automation and robotics technology are discussed. Automation of checkout, ground support, and logistics; automated software development; man-machine interfaces; neural networks; systems engineering and distributed/parallel processing architectures; and artificial intelligence/expert systems are among the topics covered