Hugo Álvarez

Providing guidance for maintenance operations using automatic markerless Augmented Reality system

This paper proposes a new real-time Augmented Reality based tool to help in disassembly for maintenance operations. This tool provides workers with augmented instructions to perform maintenance tasks more efficiently. Our prototype is a complete framework characterized by its capability to automatically generate all the necessary data from input based on untextured 3D triangle meshes, without requiring additional user intervention. An automatic offline stage extracts the basic geometric features. These are used during the online stage to compute the camera pose from a monocular image. Thus, we can handle the usual textureless 3D models used in industrial applications. A self-supplied and robust markerless tracking system that combines an edge tracker, a point based tracker and a 3D particle filter has also been designed to continuously update the camera pose. Our framework incorporates an automatic path-planning module. During the offline stage, the assembly/disassembly sequence is automatically deduced from the 3D model geometry. This information is used to generate the disassembly instructions for workers.

Towards real time 3D tracking and reconstruction on a GPU using Monte Carlo simulations

This paper addresses the problem of camera tracking and 3D reconstruction from image sequences, i.e., the monocular SLAM problem. Traditionally, this problem is solved using non-linear minimization techniques that are very accurate but hardly used in real time. This work presents a highly parallelizable random sampling approach based on Monte Carlo simulations that fits very well on the graphics hardware. The proposed algorithm achieves the same precision as non linear optimization, getting real time performance running on commodity graphics hardware. Both accuracy and performance are evaluated using synthetic data and real video sequences captured with a hand-held camera. Moreover, results are compared with an implementation of Bundle Adjustment showing that the presented method gets similar results in much less time.

Real-time deformation, registration and tracking of solids based on physical simulation

This paper proposes a novel approach to registering deformations of 3D non-rigid objects for Augmented Reality applications. Our prototype is able to handle different types of objects in real-time regardless of their geometry and appearance (with and without texture) with the support of an RGB-D camera. During an automatic offline stage, the model is processed in order to extract the data that serves as input for a physics-based simulation. Using its output, the deformations of the model are estimated by considering the simulated behaviour as a constraint. Furthermore, our framework incorporates a tracking method based on templates in order to detect the object in the scene and continuously update the camera pose without any user intervention. Therefore, it is a complete solution that extends from tracking to deformation formulation for either textured or untextured objects regardless of their geometrical shape. Our proposal focuses on providing a correct visual with a low computational cost. Experiments with real and synthetic data demonstrate the visual accuracy and the performance of our approach.

Junction assisted 3D pose retrieval of untextured 3D models in monocular images

This article presents a comprehensive framework for the recognition of untextured 3D models in a single image. The method proposed here is capable of recovering a 3D pose in a few hundred of milliseconds, which is a difficult challenge using this type of model. This proposal deals with 3D models that lack texture, so geometry features of the model are used as a basis of the 3D pose retrieval. An automatic process extracts the junctions and contours of the model, replacing the user interaction. Junctions will provide us an efficient mechanism to generate candidate matches, while contours will select the correct match based on a robust shape similarity evaluation. Our method only requires the 3D triangle mesh of the model as input, since the rest of the process is done automatically. We demonstrate the behaviour of our approach against a variety of real scenes and models. Moreover, we explain how to face the first pose problem in a robust way using a history of votes. We also present a study of the method parameterisation, describing the influence of each parameter.

A new marker design for a robust marker tracking system against occlusions

Marker systems are a widely used optical tracking method that does not support occlusions. Thus, this paper proposes a new marker design to overcome the problem of marker occlusions. It is highly adaptable, because it can be used by any marker tracking system that uses its central area to codify the digital identification. Our proposal takes advantage of an untapped frame to place some textures that will be tracked during marker occlusion. In addition, these textures are customizable, which lets users make their own designs. Two tracking methods are combined to offer a robust tracking, updating the six degrees of freedom of the camera in real time. The first one is a fast technique based on temporal coherence, whereas the second one is a robust technique based on appearance, which is used as a recovery mode. Copyright

Influence of User Grasping Position on Haptic Rendering

This paper investigates the effect of user grasping position on the performance of haptic rendering. Two dynamic models, with seven and eleven parameters, respectively, have been used to characterize the PHANToM haptic interface and the user. The parameter variability analysis shows that user grasping position significantly affects system dynamics. This variation also influences the phase margin of the system, leading to different damping factors in response to contacts with rigid virtual objects. To compensate this effect, an adaptive haptic rendering has been developed and successfully implemented, imposing a similar damping factor in the transient responses for all grip positions.

GFT: GPU fast triangulation of 3D points

Traditionally triangulating 3D points from image features is a complex task that involves non-linear optimization techniques that are computationally very expensive. This work proposes an algorithm based on Monte Carlo simulations that fits well on the graphics hardware and can perform the triangulation in real time. Results are compared against the well known Levenberg-Mardquart using real video sequences, showing that it achieves the same precision but in much less time.

Real-Time Visual Tracking of Deformable Objects in Robot-Assisted Surgery

One of the most challenging problems in robot-assisted surgical systems is to provide surgical realism at interactive simulation rates. The proposed visual tracking system can track and register object deformations in real time using a physically based formulation, despite the occlusions produced by the robotic system itself. The results obtained provide an accurate visual representation of the deformed solid and will thus enable new assistance approaches to help surgeons during surgical procedures.

Real time non-rigid 3D surface tracking using particle filter☆

Abstract Recovering a deformable 3D surface from a single image is an ill-posed problem because of the depth ambiguities. The resolution to this ambiguity normally requires prior knowledge about the most probable deformations that the surface can support. Many methods that address this problem have been proposed in the literature. Some of them rely on physical properties, while others learn the principal deformations of the object or are based on a reference textured image. However, they present some limitations such as high computational cost or the lack of the possibility of recovering the 3D shape. As an alternative to existing solutions, this paper provides a novel approach that simultaneously recovers the non-rigid 3D shape and the camera pose in real time from a single image. This proposal relies on an efficient particle filter that performs an intelligent search of a database of deformations. We present an exhaustive Design of Experiments to obtain the optimal parametrization of the particle filter, as well as a set of results to demonstrate the visual quality and the performance of our approach.

Towards a Diminished Reality System that Preserves Structures and Works in Real-time.

This paper presents a Diminished Reality system that is able to propagate textures as well as structures with a low computational cost, almost in real-time. An existing inpainting algorithm is optimized in order to reduce the high computational cost by implementing some Computer Vision techniques. Although some of the presented optimizations can be applied to a single static image directly, the global system is mainly oriented to video sequences, where temporal coherence ideas can be applied. Given that, a novel pipeline is proposed to maintain the visual quality of the reconstructed image area without the need of calculating everything again despite slow camera motions. To the best of our knowledge, the prototype presented in this paper is the only Diminished Reality system focused on structure propagation that works near real-time. Apart from the technical description, this paper presents an extensive experimental study of the system, which evaluates the optimizations in terms of time and quality.